| _ | uncertainty | _ |
| Active Recognition: Using | uncertainty | To Reduce Ambiguity |
| Applications Of A Logic Of Knowledge To Motion Planning Under | uncertainty | |
| Applying | uncertainty | Reasoning To Model Based Object Recognition |
| Automatic Grasp Planning In The Presence Of | uncertainty | |
| Autonomous Exploration Driven By | uncertainty | |
| Autonomous Exploration: Driven By | uncertainty | |
| Bayesian Modeling Of | uncertainty | In Low-Level Vision |
| Bayesian Modeling Of | uncertainty | In Low-Level Vision, Kluwer |
| Characterizing The | uncertainty | Of The Fundamental Matrix |
| Combination And Propagation Of | uncertainty | With Belief Functions--A Reexamination |
| Complexity Of Planar Compliant Motion Planning Under | uncertainty | , The |
| Complexity Of Planar Compliant Motion Planning Under | uncertainty | , The |
| Coping With | uncertainty | In Map Learning |
| Determining The Epipolar Geometry And Its | uncertainty | : A Review |
| Editorial: Reasoning With | uncertainty | In Expert Systems |
| Efficient Algorithm For One-Step Planar Compliant Motion Planning With | uncertainty | , An |
| Efficient Algorithm For One-Step Planar Compliant Motion With | uncertainty | , An |
| Ellipse Detection And Matching With | uncertainty | |
| Establishing Collision Zones For Obstacles Moving With | uncertainty | |
| Estimating Pose | uncertainty | For Surface Registration |
| Exploring Visual Constraints In The Synthesis Of | uncertainty | -Tolerant Motion Plans |
| Fast Method For Estimating The | uncertainty | In The Location Of Image Points In 3d Recognition, A |
| Feature Matching For Object Localization In The Presence Of | uncertainty | |
| Framework For Multi-Sensor Fusion In The Presence Of | uncertainty | , A |
| Framework For | uncertainty | And Validation Of 3-D Registration Methods Based On Points And Frames, A |
| Framework For | uncertainty | Reasoning In Hierarchical Visual Evidence Space, A |
| Free Space Modeling And Geometric Motion Planning Under Location | uncertainty | |
| From | uncertainty | To Visual Exploration |
| From | uncertainty | To Visual Exploration |
| Geometric Approach To Error Detection And Recovery For Robot Motion Planning With | uncertainty | , A |
| Grouping Based On Projective Geometry Constraints And | uncertainty | |
| Handling | uncertainty | In 3d Object Recognition Using Bayesian Networks |
| Hough Transform And | uncertainty | Handling. Application To Circular Object Detection In Ultrasound Medical Images |
| Image Segmentation And | uncertainty | , Wiley |
| Image Segmentation In The Presence Of | uncertainty | |
| Intrinsic Constraints In Space-Time Filtering: A New Approach To Representing | uncertainty | In Low-Level Vision |
| Localization | uncertainty | In Area-Based Stereo Algorithms |
| Mathematical Tools For Representing | uncertainty | In Perception |
| Minimum | uncertainty | Explorations In The Self-Localization Of Mobile Robots |
| Mirror | uncertainty | And Uniqueness Conditions For Determining Shape And Motion From Orthographic Projection |
| Modelling | uncertainty | In Esats By Classification Inference |
| Motion Planning With | uncertainty | : A Landmark Approach |
| On The | uncertainty | Of Straight Lines In Digital Images |
| Parallel Structure Recognition With | uncertainty | : Coupled Segmentation And Matching |
| Planning The Motion Of A Mobile Robot In A Sensory | uncertainty | Field |
| Polynomial-Time Object Recognition In The Presence Of Clutter, Occlusion, And | uncertainty | |
| Polynomial-Time Object Recognition In The Presence Of Clutter, Occlusion, And | uncertainty | |
| Predicting Object Recognition Performance Under Data | uncertainty | , Occlusion And Clutter |
| Properties Of Space-Time Sampling And The Extraction Of The Optical Flow: The Effects Of Motion | uncertainty | , The |
| Reaching A Goal With Directional | uncertainty | |
| Reasoning With | uncertainty | For Expert Systems |
| Recognizing Volumetric Objects In The Presence Of | uncertainty | |
| Reducing Positioning | uncertainty | Of Objects By Robotic Pushing |
| Reducing The Precision/ | uncertainty | Duality In The Hough Transform |
| Representation Of | uncertainty | In Computer Vision Using Fuzzy Sets |
| Representation Of | uncertainty | In Spatial Target Tracking |
| Residual | uncertainty | In Three-Dimensional Reconstruction Using Two-Planes Calibration And Stereo Methods |
| Robot Motion Planning With | uncertainty | In Control And Sensing |
| Robust Relaxation Method For Structural Matching Under | uncertainty | |
| Self-Location Of A Mobile Robot With | uncertainty | By Cooperation Of A Heading Sensor And A Ccd Tv Camera |
| Space-Time Sampling With Motion | uncertainty | : Constraints On Space-Time Filtering |
| Symmetry And Locality: | uncertainty | Revisited |
| Topology Of Locales And Its Effects On Position | uncertainty | , The |
| uncertainty | Analysis Of Image Measurements |
| uncertainty | And Inference In The Visual System |
| uncertainty | And Probability |
| uncertainty | In Artificial Intelligence, North Holland |
| uncertainty | In Interpretation Of Range Imagery |
| uncertainty | In Object Pose Determination With Three Light-Stripe Range Measurements |
| uncertainty | In Pose Estimation: A Bayesian Approach |
| uncertainty | Management For Rule-Based Systems With Applications To Image Analysis |
| uncertainty | Minimization In The Localization Of Polyhedral Objects |
| uncertainty | Of Features In Planar Object Recognition And A New Classifier |
| uncertainty | Principle In Image Processing, The |
| uncertainty | Propagation In Model-Based Recognition |
| uncertainty | Reduction Paradigm Using Structural Knowledge In Line-Drawing Understanding |
| uncertainty | Update And Dynamic Search Window For Model-Based Object Recognition |
| Unified Factorization Algorithm For Points, Line Segments And Planes With | uncertainty | Models, A |
| Unified Methodology For Motion Planning With | uncertainty | For 2d And 3d Two-Link Robot Arm Manipulators, A |
| Use Of A Priori Descriptions In A High-Level Language And Management Of The | uncertainty | In A Scene Recognition System |
| Using Backprojections For Fine Motion Planning With | uncertainty | |
| Verifying Model-Based Alignments In The Presence Of | uncertainty | |
| Visual Observation Under | uncertainty | As A Discrete Event Process |
83 for uncertainty
| _ | under | _ |
| 3-D Corridor Scene Modeling From A Single View | under | Natural Lighting Conditions |
| 3d Digital Topology | under | Binary Transformation With Applications |
| 3d Shape And Motion By Svd | under | Higher-Order Approximation Of Perspective Projection |
| Adaptive Stack Filtering | under | The Mean Absolute Error Criterion |
| Analysis Of Image Deformation | under | Orthographic Projection And Flow Parameter Estimation |
| Analysis Of Straight Homogeneous Generalized Cylinders | under | Perspective Projection |
| Analyzing A Scene'S Picture Set | under | Varying Lighting |
| Analyzing The Probability Of A False Alarm Of The Hausdorff Distance | under | Translation |
| Application Of Elliptic Fourier Descriptors To Symmetry Detection | under | Parallel Projection |
| Applications Of A Logic Of Knowledge To Motion Planning | under | Uncertainty |
| Calibrated Imaging Lab | under | Construction At Cmu, The |
| Camera Motion Parameter Recovery | under | Perspective Projection |
| Character Generation | under | Grid Constraints |
| Closed-Form Attitude Determination | under | Spectrally Varying Illumination |
| Color Constancy | under | Varying Illumination |
| Colour-Based Object Recognition | under | Spectrally Non-Uniform Illumination |
| Comparing Images | under | Variable Illumination |
| Comparing Images Using The Hausdorff Distance | under | Translation |
| Complete Object Recognition | under | Projective Distortion |
| Complexity Of Planar Compliant Motion Planning | under | Uncertainty, The |
| Complexity Of Planar Compliant Motion Planning | under | Uncertainty, The |
| Computational Approaches For Solving The Bas-Relief Ambiguity | under | Orthographic Projection |
| Computing The Minimum Hausdorff Distance Between Two Point Sets On A Line | under | Translation |
| Constraints For Interpretation Of Line Drawings | under | Perspective Projection |
| Constraints On Quadratic-Curved Features | under | Perspective Projection |
| Curve Segmentation | under | Partial Occlusion |
| Determining Motion Fields | under | Non-Uniform Illumination |
| Determining The 3-D Motion Of A Rigid Planar Patch Without Correspondence, | under | Perspective Projection |
| Determining The 3-D Motion Of A Rigid Surface Patch Without Correspondence | under | Perspective Projection: I. Planar Surfaces. Ii. Curved Surfaces. |
| Disambiguation Techniques For Recognition In Large Databases And For | under | -Constrained Reconstruction |
| Discrete Techniques For 3-D Digital Images And Patterns | under | Transformation |
| Dynamic Edge Warping: Experiments In Disparity Estimation | under | Weak Constraints |
| Efficient Algorithm To Determine The Image Of A Parallelepiped | under | A Linear Transformation, An |
| Estimation Of Color | under | Fluorescent Illuminants |
| Face Recognition | under | Varying Pose |
| Face Recognition | under | Varying Pose |
| Finding Lines | under | Bounded Error |
| Flows | under | Min/Max Curvature Flow And Mean Curvature: Applications In Image Processing |
| Free Space Modeling And Geometric Motion Planning | under | Location Uncertainty |
| From Projective To Euclidean Space | under | Any Practical Situation, A Criticism Of Self-Calibration |
| Fully Automated Face Recognition System | under | Different Conditions, A |
| Illumination Cones For Recognition | under | Variable Lighting: Faces |
| Image Processing: Flows | under | Min/Max Curvature And Mean Curvature |
| Invariant Quantities In Regression-Induced Boundaries | under | A Special Linear Transformation |
| Invariant Representation, Matching And Pose Estimation Of 3d Space Curves | under | Similarity Transformations |
| Invariant Signatures For Planar Shape Recognition | under | Partial Occlusion |
| Invariant Signatures For Planar Shape Recognition | under | Partial Occlusion |
| Laser Tracking System To Measure Position And Orientation Of Robot End Effectors | under | Motion, A |
| Lower Bound For The Edit-Distance Problem | under | An Arbitrary Cost Function, A |
| Markov Random Field Model For Object Matching | under | Contextual Constraints, A |
| Method For Shape-From-Shading Using Multiple Images Acquired | under | Different Viewing And Lighting Conditions, A |
| Mirror And Point Symmetry | under | Perspective Skewing |
| Modeling Image Center And Feature Trajectory | under | Changing Focal Length |
| Motion Constraint Equation | under | Space-Varying Or Time-Varying Illumination, A |
| Motion Estimation Algorithm | under | Time-Varying Illumination, A |
| Motion Estimation | under | Orthographic Projection |
| Motion Estimation Using Invariance | under | Group Transformations |
| New Method Of Extracting Invariants | under | Affine Transform, A |
| Non-Parametric Classification Of Pixels | under | Varying Outdoor Illumination |
| Novel Method For Detecting And Localising Of Reflectional And Rotational Symmetry | under | Weak Perspective Projection, A |
| Object Identification From Multiple Images Based On Point Matching | under | A General Transformation |
| Object Recognition Robust | under | Translations, Deformations, And Changes In Background |
| On The Deformation Of Image Intensity And Zero-Crossing Contours | under | Motion |
| On The Uniqueness Of Correspondence | under | Orthographic And Perspective Projections |
| Optimal Algorithm For Finding The Edge Visibility Polygon | under | Limited Visibility, An |
| Optimal Error Discretization | under | Depth And Range Constraints |
| Optimal Geometric Model Matching | under | Full 3d Perspective |
| Optimal Likelihood Generators For Edge Detection | under | Gaussian Additive Noise |
| Optimal Parallel Stack Filtering | under | The Mean Absolute Error Criterion |
| Optimal Shape Coding | under | Buffer Constraints |
| Performance Characterization Of Fundamental Matrix Estimation | under | Image Degradation |
| Photorealistic Image Synthesis For Outdoor Scenery | under | Various Atmospheric Conditions |
| Point Configuration Invariants | under | Simultaneous Projective And Permutation Transformations |
| Point/Line Correspondence | under | 2d Projective Transformation |
| Polygon Containment | under | Translation |
| Predicting Object Recognition Performance | under | Data Uncertainty, Occlusion And Clutter |
| Preservation Of Topological Properties Of A Simple Closed Curve | under | Digitalization |
| Quantitative Performance Evaluation Of Thinning Algorithms | under | Noisy Conditions |
| Recognition Of Planar Shapes | under | Affine Distortion |
| Recognize The Similarity Between Shapes | under | Affine Transformation |
| Recognizing Novel 3-D Objects | under | New Illumination And Viewing Position Using A Small Number Of Example Views Or Even A Single View |
| Reconstructible Pairs Of Incomplete Polyhedral Line Drawings | under | General Reconstruction Procedure |
| Reconstructing Shape From Shading Images | under | Point Light Source Illumination |
| Restoration Of Digital Images | under | Additive Noises Using A Quality Measure Of Restored Images |
| Rigid Body Segmentation And Shape Description From Dense Optical Flow | under | Weak Perspective |
| Rigid Body Segmentation And Shape Description From Dense Optical Flow | under | Weak Perspective |
| Rigidity Checking Of 3d Point Correspondences | under | Perspective Projection |
| Rigidity Checking Of 3d Point Correspondences | under | Perspective Projection |
| Robust Relaxation Method For Structural Matching | under | Uncertainty |
| Robustness Of Image Pyramids | under | Structural Perturbations |
| Sensorimotor Action Sequence Learning With Application To Face Recognition | under | Discourse |
| Shape And Motion From Image Streams | under | Orthography: A Factorization Method |
| Shape From Angles | under | Perspective Projection |
| Shape From Darkness | under | Error |
| Shape From Shading With Interreflections | under | A Proximal Light Source: Distortion-Free Copying Of An Unfolded Book |
| Shape From Shading With Interreflections | under | Proximal Light Source: 3d Shape Reconstruction Of Unfolded Book Surface From A Scanner Image |
| Shape From Shadows | under | Error |
| Shape Recognition | under | Affine Distortions |
| Site Model Acquisition | under | The Umass Radius Project |
| Smoothing The Optic Flow Field | under | Perspective Projection |
| Space Requirements Of Indexing | under | Perspective Projections, The |
| Stability Invariance Of Discrete And Continuous Multidimensional Systems | under | Some Variable Transformations |
| Statistical Change Detection With Moments | under | Time-Varying Illumination |
| Stochastic Formulations Of Optical Flow Algorithms | under | Variable Brightness Conditions |
| Structure And Motion Estimation From Dynamic Silhouettes | under | Perspective Projection |
| Structure And Motion From Optical Flow | under | Orthographic Projection |
| Structure And Motion From Optical Flow | under | Perspective Projection |
| Structure-From-Motion | under | Orthographic Projection |
| Structure-From-Motion | under | Orthographic Projection |
| Supervised Learning Of Smoothing Parameters In Image Restoration By Regularization | under | Cellular Neural Networks Framework |
| Time-Optimal Motion Of Two Omnidirectional Robots Carrying A Ladder | under | A Velocity Constraint |
| Toward Accurate Recovery Of Shape From Shading | under | Diffuse Lighting |
| Towards Absolute Invariants Of Images | under | Translation, Rotation, And Dilation |
| Towards Accurate Recovery Of Shape From Shading | under | Diffuse Lighting |
| Two-Dimensional On-Line Tessellation Acceptors Are Not Closed | under | Complement |
| Unified Sun And Sky Illumination For Shadows | under | Trees |
| Uniqueness Of 3d Pose | under | Weak Perspective: A Geometrical Proof |
| Video Augmentation By Image-Based Rendering | under | The Perspective Camera Model |
| Visual Motion Analysis | under | Interceptive Behavior |
| Visual Observation | under | Uncertainty As A Discrete Event Process |
| What Is The Set Of Images Of An Object | under | All Possible Illumination Conditions? |
| What Is The Set Of Images Of An Object | under | All Possible Lighting Conditions? |
122 for under
| _ | understanding | _ |
| 3-D Motion Estimation, | understanding | , And Prediction From Noisy Image Sequences |
| 3-D Motion From Image Sequences: Modeling, | understanding | , And Prediction |
| 3d Cuboid Scene | understanding | By A Mixed Cognitive Graph And Log-Complex Mapping Paradigm |
| 3d Mosaic Scene | understanding | System, The |
| 3d Mosaic Scene | understanding | System: Incremental Reconstruction Of 3d Scenes From Complex Images, The |
| Abstract Data Types And Multiprocessor Architecture For Image | understanding | |
| Adaptive Image Exploitation: Image | understanding | At Raytheon |
| Advances In Image | understanding | --A Festchrift For Azriel Rosenfeld, Ieee Computer Society Press, Los Alamitos |
| Algorithm Database For An Image | understanding | Task Execution Environment, An |
| Approximate Reasoning And Knowledge In Nmr Image | understanding | |
| Architectural Requirements Of Image | understanding | With Respect To Parallel Processing |
| Artificial Neural Networks For Image | understanding | , Van Nostrand |
| Causal Scene | understanding | |
| Cmu Image | understanding | Program |
| Cmu Image | understanding | Program |
| Cmu Image | understanding | Research |
| Complexity Of | understanding | Line Drawings Of Origami Scenes, The |
| Computational Models For Image | understanding | |
| Constructs For Cooperative Image | understanding | Environments |
| Context Knowledge And Search Control Issues In Object-Oriented Prolog-Based Image | understanding | |
| Cooperative Spatial Reasoning For Image | understanding | |
| Darpa Image | understanding | Benchmark For Parallel Computers, The |
| Darpa Image | understanding | Benchmark Workshop, Avon, Ct |
| Database Support For Exploitation Image | understanding | |
| Design And Implementation Of A Distributed Image | understanding | System, The |
| Design Of A Knowledge-Based System For | understanding | Electronic Circuit Diagrams |
| Developing The Aspect Graph Representation For Use In Image | understanding | |
| Development Of The Image | understanding | Environment, The |
| Dipod: An Image | understanding | Development And Implementation System |
| Document | understanding | System |
| Document | understanding | System Incorporating With Character Recognition, A |
| Drawing Image | understanding | Using State Transition Models |
| Dynamic Scene | understanding | For Autonomous Mobile Robots |
| Efficient Diagram | understanding | With Characteristic Pattern Detection |
| Efficient Image | understanding | Based On The Markov Random Field Model And Error Backpropagation Network |
| Environment | understanding | Of Mobile Robot ``Harunobu-3'' By Picture Interpretation Language Pils V-3 |
| Ernest: A Semantic Network System For Pattern | understanding | |
| Evidence Accumulation For Spatial Reasoning In Aerial Image | understanding | |
| Exploiting Neural Trees In Range Image | understanding | |
| Extraction Of Micro-Terrain Ravines Using Image | understanding | Constrained By Topographic Context |
| Extremal Mesh And The | understanding | Of 3d Surfaces, The |
| Face Perspective | understanding | Using Artificial Neural Network Group-Based Tree |
| Fifth German-Russian Workshop On Pattern Recognition And Image | understanding | , Herrsching, Germany |
| From Inspection To Process | understanding | And Monitoring: A View On Computer Vision In Manufacturing |
| Future Directions In Computer Vision And Image | understanding | : Etl Perspectives |
| General Routing On The Lowest Level Of The Image | understanding | Architecture |
| Generating Dynamic Projection Images For Scene Representation And | understanding | |
| Generation Of Sketch Map Image And Its Instructions To Support The | understanding | Of Geographical Information |
| Group Theoretical Methods In Image | understanding | , Springer |
| Guest Ed., (Special Section On) Image | understanding | |
| Guest Ed., Special Issue On Character Recognition And Document | understanding | |
| Guest Ed., Special Issue On Image Processing And | understanding | (Papers From The First Japan-Korea Joint Conference On Computer Vision, Seoul, Korea, October 10-11, 1991) |
| Guest Ed., Special Issue On Machine Vision And Image | understanding | , (Papers From The Ieee Systems, Man, And Cybernetics Conference, Alexandria, Va, October 20-23, 1987) |
| Guest Ed., Special Issue: Image | understanding | Research At The University Of Maryland |
| Guest Ed., Special Issue: | understanding | Shape: Perspectives From Natural And Machine Vision, Ivc 11(6) |
| Guest Eds., (Special Issue On) Parallel Processing For Computer Vision And Image | understanding | |
| Guest Eds., (Special Issue On) Range Image | understanding | |
| Guest Eds., Special Issue On Document Image | understanding | And Retrieval |
| Hierarchical Inference Scheme For High-Level Image | understanding | |
| Homogeneous Architecture For Knowledge Based Image | understanding | Systems, A |
| Human Image | understanding | : Recent Research And A Theory |
| Human Movement | understanding | , North-Holland |
| Hypothesis Integration In Image | understanding | Systems |
| Image Sensing, Processing, And | understanding | For Control And Guidance Of Aerospace Vehicles (Orlando, Fl, April 5 |
| Image | understanding | 1984, Ablex, Norwood |
| Image | understanding | 1985-86, Ablex, Norwood |
| Image | understanding | 1989, Ablex, Norwood |
| Image | understanding | And Machine Vision (Optical Society Of America Topical Meeting, North Falmouth, Ma, June 12-14, 1989), Optical Society Of America |
| Image | understanding | And Robotics Research At Columbia University |
| Image | understanding | And Robotics Research At Columbia University |
| Image | understanding | And Robotics Research At Columbia University |
| Image | understanding | And Robotics Research At Columbia University |
| Image | understanding | And The Man-Machine Interface (Los Angeles, Ca, January 15-16 |
| Image | understanding | And The Man-Machine Interface Iii (Orlando, Fl, April 3-4 |
| Image | understanding | Architecture, The |
| Image | understanding | Architecture, The |
| Image | understanding | Architecture: Exploiting Potential Parallelism In Machine Vision |
| Image | understanding | At Cmu |
| Image | understanding | At Cornell University |
| Image | understanding | At Iit |
| Image | understanding | At Lockheed Martin Management And Data Systems |
| Image | understanding | At Lockheed Martin Valley Forge |
| Image | understanding | At The Grasp Laboratory |
| Image | understanding | At The University Of Rochester |
| Image | understanding | At The University Of Rochester |
| Image | understanding | Environment Program, The |
| Image | understanding | Environment Program, The |
| Image | understanding | Environment Progress Since Iuw'96, The |
| Image | understanding | Environment Service Model: An Elegant Approach To Providing Class Services, The |
| Image | understanding | Environment: Data Exchange, The |
| Image | understanding | Environment: Image Features, The |
| Image | understanding | Environment: Overview, The |
| Image | understanding | Environment: Progress Since Iuw '97, The |
| Image | understanding | Environments |
| Image | understanding | For Aerospace Applications (Munich, Germany, June 13-14 |
| Image | understanding | From Thermal Emission Polarization |
| Image | understanding | From Thermal Emission Polarization |
| Image | understanding | In The '90s: Building Systems That Work (Proceedings Of The Aipr Workshop, Mclean, Va, October 18-19 |
| Image | understanding | In Unstructured Environment (Erice-Trapani, Sicily, January 5-25, 1987), World Scientific |
| Image | understanding | Performance Study On The Icl Distributed Array Processor, An |
| Image | understanding | Research At Brown University |
| Image | understanding | Research At Carnegie Mellon |
| Image | understanding | Research At Cmu |
| Image | understanding | Research At Cmu |
| Image | understanding | Research At Cmu |
| Image | understanding | Research At Cmu: From Vision Science To Autonomous Systems |
| Image | understanding | Research At Colorado State University |
| Image | understanding | Research At Columbia Univeristy |
| Image | understanding | Research At Columbia University |
| Image | understanding | Research At Columbia University |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At Ge |
| Image | understanding | Research At General Electric |
| Image | understanding | Research At Honeywell |
| Image | understanding | Research At Hughes Aircraft Company: Adaptive Image Exploitation |
| Image | understanding | Research At Johns Hopkins |
| Image | understanding | Research At Johns Hopkins |
| Image | understanding | Research At Johns Hopkins |
| Image | understanding | Research At Rochester |
| Image | understanding | Research At Rochester |
| Image | understanding | Research At Rochester |
| Image | understanding | Research At Rochester |
| Image | understanding | Research At Rochester |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At Sri International |
| Image | understanding | Research At The Georgia Institute Of Technology |
| Image | understanding | Research At The University Of Maryland (December 1986 - January 1988) |
| Image | understanding | Research At The University Of Maryland (January 1988-February 1989) |
| Image | understanding | Research At The University Of Maryland: Video Surveillance And Tracking |
| Image | understanding | Research At The University Of Utah |
| Image | understanding | Research At Ti |
| Image | understanding | Research At Uc Irvine: Automated Invariant Recognition In Hyperspectral Imagery |
| Image | understanding | Research At Uc Irvine: Automatic Recognition In Multispectral Imagery |
| Image | understanding | Research At Uc Riverside |
| Image | understanding | Research At Uc Riverside: Integrated Recognition, Learning And Image Databases |
| Image | understanding | Research At Uc Riverside: Robust Recognition Of Objects In Real-World Scenes |
| Image | understanding | Research At University Of Washington |
| Image | understanding | Research For Automatic Target Recognition |
| Image | understanding | Research For Battle,Eld Awareness At Johns Hopkins University |
| Image | understanding | Research For Battlefield Awareness At Johns Hopkins University |
| Image | understanding | Strategies: Application To Electron Microscopy |
| Image | understanding | System For Carotid Angiograms |
| Image | understanding | System Using Attributed Symbolic Representation And Inexact Graph Matching, An |
| Image | understanding | Technology And Its Transition To Military Applications |
| Image | understanding | Tools |
| Image | understanding | Via Representation Of The Projected Motion Group |
| Image | understanding | Via Texture Analysis |
| Image | understanding | Workshop, Los Angeles, Ca, February 23-25, 1987. (Proceedings Published By Morgan Kaufmann |
| Image | understanding | : Intelligent Systems |
| Image | understanding | : Intelligent Systems |
| Image | understanding | : Intellligent Systems |
| Imagery Exploitation Applications For Image | understanding | |
| Images And | understanding | , Cambridge University Press, Cambridge |
| Information Fusion In Image | understanding | |
| Initial Hypothesis Formation In Image | understanding | Using An Automatically Generated Knowledge Base |
| Integra-An Integrated Approach To Range Image | understanding | |
| Integra-An Integrated System For Range Image | understanding | |
| Integrated Approach For Scene | understanding | Based On Markov Random Field Model, An |
| Integrated Image | understanding | Benchmark: Recognition Of A 2-1/2d ``Mobile'', An |
| Integrated Recognition, Learning And Image Databases: Image | understanding | Research At Uc Riverside |
| Integration Of Image | understanding | Exploitation Algorithms In The Radius Testbed |
| Intelligent Image Interface To 3d Image | understanding | And Presentation |
| Intelligent Operating System For Executing Image | understanding | Tasks On A Reconfigurable Parallel Architecture, An |
| Knowledge Organization And Control Structure In Image | understanding | |
| Knowledge-Based Aerial Image | understanding | Systems And Expert Systems For Image Processing |
| Knowledge-Based Image | understanding | Systems: A Survey |
| Knowledge-Based Image | understanding | Using Incomplete And Generic Models |
| Knowledge-Based Pattern | understanding | |
| Knowledge-Based Picture | understanding | Of Weather Charts |
| Knowledge-Based Segmentation Method For Document | understanding | , A |
| Knowledge-Based | understanding | Of Road Maps And Other Line Images |
| Krus: A Knowledge-Based Road Scene | understanding | System |
| Learning Of Visual Modules From Examples: A Framework For | understanding | Adaptive Visual Performance |
| Lee S. Baumann, Ed., Proceedings: Image | understanding | Workshop (New Orleans, La, October 3-4 |
| Long-Range Spatiotemporal Motion | understanding | Using Spatiotemporal Flow Curves |
| Machine Learning Paradigms For Pattern Recognition And Image | understanding | |
| Machine | understanding | Of Csg: Extraction And Unification Of Manufacturing Features |
| Machine | understanding | Of Human Action |
| Macsym: A Hierarchical Parallel Image Processing System For Event Driven Pattern | understanding | Of Documents |
| Maryland Approach To Image | understanding | , The |
| Maryland Progress In Image | understanding | |
| Maryland Progress In Image | understanding | |
| Maryland Progress In Image | understanding | |
| Maryland Progress In Image | understanding | |
| Medical Image | understanding | And Analysis, Leeds, Uk |
| Medical Image | understanding | And Analysis, Oxford, England |
| Method For Initial Hypothesis Formation In Image | understanding | , A |
| Model For An Intelligent Operating System For Executing Image | understanding | Tasks On A Reconfigurable Parallel Architecture, A |
| Model Invocation For Three Dimensional Scene | understanding | |
| Model-Supported Exploitation As A Framework For Image | understanding | |
| Modular Object Oriented Image | understanding | Environment, A |
| Motion | understanding | From Qualitative Visual Dynamics |
| Motion | understanding | Meets Early Vision: An Introduction |
| Motion | understanding | : Robot And Human Vision, Kluwer, Boston |
| Multidisciplinary Image | understanding | Research At The University Of Maryland |
| Multiple-Level Heterogeneous Architecture For Image | understanding | , A |
| Multiscale Image | understanding | |
| Nato Advanced Study Institute On Vision And Image | understanding | , Erice, Sicily |
| Next Generation Image | understanding | Architecture, The |
| Nsf Workshop On Range Image | understanding | , East Lansing, Mi |
| Optimal Algorithms For Image | understanding | : Current Status And Future Plans |
| Orthogonal Multiprocessor Sharing Memory With An Enhanced Mesh For Integrated Image | understanding | |
| Overview Of Architecture Research For Image | understanding | At The University Of Massachusetts, An |
| Panoramic Representation Of Scenes For Route | understanding | |
| Parallel Any-Time Control Algorithm For Image | understanding | , A |
| Parallel Architectures And Algorithms For Image | understanding | , Academic Press |
| Parallel Dense Depth From Motion On An Image | understanding | Architecture |
| Parallel Dense Depth From Motion On The Image | understanding | Architecture |
| Physical Approach To Color Image | understanding | , A |
| Physical Approach To Color Image | understanding | , A.K. Peters, Wellesley, A |
| Physical Approach To Color Image | understanding | , Jones & Bartlett, A |
| Physics-Based Visual | understanding | |
| Planning For The Efficient Employment Of Image | understanding | Assets |
| Polarization Vision: A New Sensory Approach To Image | understanding | |
| Primary Algorithm For The | understanding | Of Logic Circuit Diagrams, A |
| Problem-Independent Control Algorithm For Image | understanding | , A |
| Proceedings, Image | understanding | Workshop (Cambridge, Ma, April 6-8, 1988), Morgan Kaufmann, San Mateo |
| Proceedings, Image | understanding | Workshop (Palo Alto, Ca, May 23-26, 1989), Morgan Kaufmann |
| Proceedings, Symposium On Document Image | understanding | Technology, Annapolis, Md |
| Proceedings, [Arpa] Image | understanding | Workshop (Monterey, Ca, November 13-16, 1994), Morgan Kaufmann, San Francisco |
| Proceedings, [Arpa] Image | understanding | Workshop (Washington, Dc, April 18-21, 1993), Morgan Kaufmann, San Mateo |
| Proceedings, [Darpa] Image | understanding | Workshop, Monterey, Ca |
| Proceedings, [Darpa] Image | understanding | Workshop, New Orleans, La |
| Proceedings, [Darpa] Image | understanding | Workshop, Palm Springs, Ca |
| Proceedings, [Darpa] Image | understanding | Workshop, San Diego, Ca, January 26-29, 1992 (Morgan Kaufmann |
| Proceedings: Image | understanding | Workshop (Miami Beach, Fl |
| Proceedings: [Darpa] Image | understanding | Workshop, Pittsburgh, Pa, September 11-13, 1990 (Morgan Kaufmann |
| Programming In The Image | understanding | Environment: Locating Fibers In Microscope Images |
| Progress In Image | understanding | At Brown University |
| Progress In Image | understanding | At Mit |
| Progress In Image | understanding | At Mit |
| Progress In Image | understanding | At The University Of Rochester |
| Progress Toward An Image | understanding | Application Development Environment |
| Qualitative Approach To Dynamic Scene | understanding | , A |
| Qualitative Motion | understanding | |
| Qualitative Motion | understanding | , Kluwer |
| Qualitative | understanding | Of Scene Dynamics For Mobile Robots |
| Radius: Image | understanding | For Imagery Intelligence, Morgan Kaufmann, San Francisco |
| Radius: Research And Development For Image | understanding | Systems Phase 1 |
| Range Image | understanding | |
| Range Image | understanding | , Springer |
| Real-Time Recognition And Visual Control: Image | understanding | Research At Rochester |
| Realistic Image Synthesis Of A Deformable Living Thing Based On Motion | understanding | |
| Recent Progress Of The Rochester Image | understanding | Project |
| Recognition Approach To Gesture Language | understanding | |
| Recognition Of 3-D Objects Via Spatial | understanding | Of 2-D Images |
| Recovery And | understanding | Of A Line Drawing From Indoor Scenes, The |
| Report On Range Image | understanding | Workshop, East Lansing, Michigan, March 21-23, 1988 |
| Report On The Darpa Image | understanding | Architectures Workshop (Mclean, Va, November 13-14, 1986), A |
| Report On The Results Of The Darpa Integrated Image | understanding | Benchmark Exercise, A |
| Research In Image | understanding | And Automated Cartography: 1997-1998 |
| Rule-Based System For Document | understanding | , A |
| Scene | understanding | By Rule Evaluation |
| Scene | understanding | From Propagation And Consistency Of Polarization-Based Constraints |
| Second Darpa Image | understanding | Benchmark On Warp And Extending Apply To Include Global Operations, The |
| Second Sdrv Workshop (Slovenian Society For Pattern Recognition), Speech And Image | understanding | , Ljubljana, Slovenia |
| Seeing And | understanding | : Representing The Visual World |
| Semantic Network Array Processor And Its Applications To Image | understanding | |
| Semantic Network Array Processor And Its Applications To Image | understanding | |
| Semantic Networks For | understanding | Scenes, Plenum |
| Shape | understanding | From Lambertian Photometric Flow Fields |
| Shape | understanding | From Lambertian Photometric Flow Fields |
| Sigma Image | understanding | System, The |
| Sigma-A Knowledge-Based Aerial Image | understanding | System, Van Nostrand |
| Sigma: A Framework For Image | understanding | - Integration Of Bottom-Up And Top-Down Analyses |
| Situated Image | understanding | In A Multiagent Framework |
| Solving Diverse Image | understanding | Problems Using The Image Understanding Environment |
| Solving Diverse Image | understanding | Problems Using The Image Understanding Environment |
| Some Aspects Of An Image | understanding | Database For An Intelligent Operating System |
| Some Sample Algorithms For The Image | understanding | Architecture |
| Spatial Database Manager For A Multi-Source Image | understanding | System |
| Spatial Objects In The Image | understanding | Environment |
| Spatial | understanding | : The Successor System |
| Staff, Mit Progress In | understanding | Images, The |
| Staff, Mit Progress In | understanding | Images, The |
| Staff, Mit Progress In | understanding | Images, The |
| Staff, Mit Progress In | understanding | Images, The |
| Staff, Progress In Image | understanding | At Mit |
| Staff, Progress In Image | understanding | At Mit |
| Status And Current Research In The Image | understanding | Architecture Effort |
| Status And Current Research In The Image | understanding | Architecture Program |
| Strategies For Diagram | understanding | : Generalized Equivalence, Spatial/Object Pyramids And Animate Vision |
| Summary Of Image | understanding | Research At The University Of Massachusetts |
| Summary Of Progress In Image | understanding | At The University Of Massachusetts |
| Surfaces In Range Image | understanding | , Springer |
| Symposium On Document Image | understanding | Technology, Bowie, Md |
| Talking About 3d Scenes: Integration Of Image And Speech | understanding | In A Hybrid Distributed System |
| Three-Dimensional Vlsi Architecture For Image | understanding | |
| Topology-Based Component Extractor For | understanding | Electronic Circuit Diagrams, A |
| Toward A Fundamental | understanding | Of Multiresolution Sar Signatures |
| Umass Image | understanding | Architecture, The |
| Uncertainty Reduction Paradigm Using Structural Knowledge In Line-Drawing | understanding | |
| understanding | Assembly Illustrations In An Assembly Manual Without Any Model Of Mechanical Parts |
| understanding | Human Motion Patterns |
| understanding | Images--Finding Meaning In Digital Imagery, Springer |
| understanding | Images-The Search For Meaning In Visualization, Springer |
| understanding | Neural Networks-Computer Explorations, Mit Press, Cambridge |
| understanding | Noise: The Critical Role Of Motion Error In Scene Reconstruction |
| understanding | Noise: The Critical Role Of Motion Error In Scene Reconstruction |
| understanding | Object Configurations Using Range Images |
| understanding | Object Motion |
| understanding | Object Motion |
| understanding | Objects With Curved Surfaces From A Single Perspective View Of Boundaries |
| understanding | People Pointing: The Perseus System |
| understanding | Positioning From Multiple Images |
| understanding | Scene Descriptions By Integrating Different Sources Of Knowledge |
| understanding | Scene Dynamics |
| understanding | Synthetic Aperture Radar Images |
| understanding | Synthetic Aperture Radar Images, Artech House |
| understanding | The Hough Transform: Hough Cell Support And Its Utilisation |
| understanding | The Relationship Between The Optimization Criteria In Two-View Motion Analysis |
| understanding | The Shape Properties Of Trihedral Polyhedra |
| understanding | The Structure Of Diffuse Scale-Spaces |
| understanding | Three Dimensional Images --Recognition Of Abdominal Anatomy From Cat Scans, Umi Research Press, Ann Arbor |
| understanding | Three-Dimensional Images-Recognition Of Abdominal Anatomy From Cat Scans, Umi Research Press, Ann Arbor |
| understanding | Three-View Drawings Based On Heuristics |
| understanding | Vision, Academic Press |
| understanding | Vision: An Interdisciplinary Perspective, Mind & Language 5(4) |
| Unified Approach For Early-Phase Image | understanding | Using A General Decision Criterion |
| Usc Image | understanding | Research |
| Usc Image | understanding | Research-1986 |
| Usc Image | understanding | Research: 1988-89 |
| Usc Image | understanding | Research: 1989-1990 |
| Usc Image | understanding | Research: 1990-1991 |
| Usc Image | understanding | Research: 1992-1993 |
| Usc Image | understanding | Research: 1993-1994 |
| Usc Image | understanding | Research: 1994-1995 |
| Use And Representation Of Knowledge In Image | understanding | Based On Semantic Networks |
| User Interface Representations For Image | understanding | |
| Using Expert Systems For Image | understanding | |
| Using Geometrical Information For Accurate Scene | understanding | In An Artificial Vision System |
| Veil: Combining Semantic Knowledge With Image | understanding | |
| Video Skimming And Characterization Through The Combination Of Image And Language | understanding | Techniques |
| Video Skimming And Characterization Through The Combination Of Image And Language | understanding | Techniques |
| Visions Image- | understanding | System, The |
| Visiting Card | understanding | System |
| Visual Dynamic Scene | understanding | Exploiting High-Level Spatio-Temporal Models |
| Visual Hull Concept For Silhouette-Based Image | understanding | , The |
| Vsam At The Mit Media Laboratory And Cbcl: Learning And | understanding | Action In Video Imagery |
| Vsam At The Mit Media Laboratory And Cbcl: Learning And | understanding | Action In Video Imagery Pi Report 1998 |
| What-And-Where Filter | A Spatial Mapping Neural Network For Object Recognition And Image | understanding | , The |
| Wisard: A Component For Image | understanding | Architectures |
| `Hard-Copy' Benchmark Suite For Image | understanding | In Manufacturing |
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| _ | unified | _ |
| 3d Shape And Motion Analysis From Image Blur And Smear: A | unified | Approach |
| Absolute Orientation From Uncertain Point Data: A | unified | Approach |
| Agglomerative Clustering On Range Data With A | unified | Probabilistic Merging Function And Termination Criterion |
| Analytical Studies Of Low-Level Motion Estimators In Space-Time Images Using A | unified | Filter Concept |
| Automatic Target Detection And Recognition In Multiband Imagery: A | unified | Ml Detection And Estimation |
| Biased Anisotropic Diffusion-A | unified | Regularization And Diffusion Approach To Edge Detection |
| Biased Anisotropic Diffusion: A | unified | Regularization And Diffusion Approach To Edge Detection |
| Computer Vision-A | unified | , Biologically Inspired Approach, North-Holland |
| Computer Vision-A | unified | , Biologically-Inspired Approach, Elsevier |
| Content-Based Video Retrieval And Compression: A | unified | Solution |
| Direct Recovering Of Nth Order Surface Structure Using | unified | Optical Flow Field |
| Extension Of Canny'S Discrete Criteria To Second Derivative Filters | Towards A | unified | Approach |
| Filters, Random Fields And Maximum Entropy (Frame): Towards A | unified | Theory For Texture Modeling |
| Frame: Filters, Random Fields And Maximum Entropy--Towards A | unified | Theory For Texture Modeling |
| Gaussian Decomposition Of Two-Dimensional Shapes: A | unified | Representation For Cad And Vision Applications |
| Image-Flow Computation: An Estimation-Theoretic Framework And A | unified | Perspective |
| Lines And Points In Three Views-A | unified | Approach |
| Local Criteria: A | unified | Approach To Local Adaptive Linear And Rank Filters For Image Restoration And Enhancement |
| Moment-Based | unified | Approach To Image Feature Detection, A |
| On | unified | Optical Flow Field |
| Optic Flow Computation: A | unified | Perspective, Ieee Computer Society Press, Los Alamitos |
| Quadtrees, Octrees, Hyperoctrees: A | unified | Analytical Approach To Tree Data Structures Used In Graphics, Geometric Modeling, And Image Processing |
| Towards A | unified | Iu Environment: Coordination Of Existing Iu Tools With The Iue |
| Two Plane Camera Calibration: A | unified | Model |
| unified | 3d Models For Multisensor Image Synthesis |
| unified | Algorithm For Boolean Shape Operations, A |
| unified | Algorithm For Sorting On Multidimensional Mesh-Connected Processors, A |
| unified | Approach For Early-Phase Image Understanding Using A General Decision Criterion |
| unified | Approach For Image Segmentation Using Exact Statistics, A |
| unified | Approach For Robot Motion Planning With Moving Polyhedral Obstacles, A |
| unified | Approach To Artificial Intelligence, Pattern Recognition, Image Processing And Computer Vision In Fifth-Generation Computer Systems, A |
| unified | Approach To Boundary Perception: Edges, Textures, And Illusory Contours, A |
| unified | Approach To Camera Fixation And Vision-Based Road Following, A |
| unified | Approach To Coding And Interpreting Face Images, A |
| unified | Approach To Iconic Indexing, Retrieval, And Maintenance Of Spatial Relationships In Image Databases, A |
| unified | Approach To Moving Object Detection In 2d And 3d Scenes, A |
| unified | Approach To Moving Object Detection In 2d And 3d Scenes, A |
| unified | Approach To Moving Object Detection In 2d And 3d Scenes, A |
| unified | Approach To Noise Removal, Image Enhancement, And Shape Recovery, A |
| unified | Approach To Noniterative Linear Signal Restoration, A |
| unified | Approach To Pattern Recognition, A |
| unified | Approach To Segmentation Of Grey-Level And Dot-Pattern Images, A |
| unified | Approach To The Change Of Resolution: Space And Gray-Level, A |
| unified | Approach To The Linear Camera Calibration Problem, A |
| unified | Approach To The Linear Camera Calibration Problem, A |
| unified | Approach To Visibility Representations Of Planar Graphs, A |
| unified | Approach To Volumetric Registration And Integration Of Multiple Range Images, A |
| unified | Bayesian Framework For Face Recognition, A |
| unified | Computational Framework For Minkowski Operations, A |
| unified | Computational Theory For Motion Transparency And Motion Boundaries Based On Eigenenergy Analysis, A |
| unified | Description And Recognition Of Continuous Contours And Regions |
| unified | Distance Transform Algorithm And Architecture, A |
| unified | Factorization Algorithm For Points, Line Segments And Planes With Uncertainty Models, A |
| unified | Formulation Of A Class Of Image Thresholding Techniques |
| unified | Framework To Recover 3-D Surfaces By Combining Image-Based And Externally-Supplied Constraints, A |
| unified | Linear-Time Algorithm For Computing Distance Maps, A |
| unified | Methodology For Motion Planning With Uncertainty For 2d And 3d Two-Link Robot Arm Manipulators, A |
| unified | Mixture Framework For Motion Segmentation: Incorporating Spatial Coherence And Estimating The Number Of Models, A |
| unified | Modeling Of Non-Homogeneous 3d Objects For Thermal And Visual Image Synthesis |
| unified | Neural Network Approach To Digital Image Halftoning, A |
| unified | Optical Flow Field Approach To Motion Analysis From A Sequence Of Stereo Images |
| unified | Perspective On Computational Techniques For The Measurement Of Visual Motion, A |
| unified | Perspective On Computational Techniques For The Measurement Of Visual Motion, A |
| unified | Structural-Stochastic Model For Texture Analysis And Synthesis, A |
| unified | Sun And Sky Illumination For Shadows Under Trees |
| unified | Theory Of Structure From Motion, A |
| unified | Theory Of Uncalibrated Stereo For Both Perspective And Affine Cameras, A |
| unified | , Multiresolution Framework For Automatic Target Recognition, A |
| unified | , Multiresolution Framework For Automatic Target Recognition, A |
| Visual Motion Estimation From Point Features: | unified | View |
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| _ | university | _ |
| 21st International Conference On Parallel Processing, | university | Park, Pa |
| Aerial And Ground-Based Video Surveillance At Cornell | university | |
| Affine Analysis Of Image Sequences, Cambridge | university | Press, Cambridge |
| Algorithmic Geometry, Cambridge | university | Press, Cambridge |
| Autbild '84/2 (Automatische Bildverarbeitung, Wandlitzsee, Ddr, November 5-9, 1984), Friedrich Schiller | university | , Jena |
| Autbild '85/3 (Automatische Bildverarbeitung, Wandlitzsee, Ddr, September 23-27, 1985), Friedrich Schiller | university | , Jena |
| Automated Vision And Sensing Systems At Boston | university | |
| Automated Vision And Sensing Systems At Boston | university | |
| Biophysics Of Computation|Information Processing In Single Neurons, Oxford | university | Press |
| Computational Geometry In C, Cambridge | university | Press, Cambridge |
| Computer Vision And Image Analysis, Symposium In Memory Of P.R. Krishnaiah And C.G. Khatri, | university | Park, Pa |
| Computer Vision And Image Processing Research At The | university | Of Texas At Austin |
| Computer Vision At The Hebrew | university | |
| Computer Vision Research At The | university | Of Maryland: A 20-Year Retrospective |
| Computer Vision Research At The | university | Of Massachusetts-Themes And Progress |
| Computer Vision Research At The | university | Of Washington |
| Corticonics: Neural Circuits Of The Cerebral Cortex, Cambridge | university | Press, Cambridge |
| Creative Computer Graphics, Cambridge | university | Press, Cambridge |
| Davenport-Schinzel Sequences And Their Geometric Applications, Cambridge | university | Press, Cambridge |
| Discrete Relaxation Techniques, Oxford | university | Press, Oxford |
| Early Visual Development-Normal And Abnormal, Oxford | university | Press, Oxford |
| Foundations Of Artificial Intelligence-A Sourcebook, Cambridge | university | Press, Cambridge, The |
| From Living Eyes To Seeing Machines, Oxford | university | Press, Oxford |
| Frontiers In Handwriting Recognition (Proceedings Of An International Workshop, Montreal, Canada, April 2-3, 1990), Concordia | university | |
| General Pattern Theory|A Mathematical Study Of Regular Structures, Oxford | university | Press |
| Geometric Computation For Machine Vision, Oxford | university | Press, Oxford |
| Geometric Tomography, Cambridge | university | Press, Cambridge |
| Geometry Of Fractal Sets, Cambridge | university | Press, Cambridge, The |
| Graphics Recognition--Methods And Applications (Selected Papers From The First International Workshop, | university | Park, Pa, August 10-11, 1995), Springer |
| Gray-Scale Measurements In Multi-Dimensional Digitized Images, Delft | university | Press, Delft |
| Guest Ed., Introduction: Vision As Intelligent Behavior-An Introduction To Machine Vision At The | university | Of Rochester |
| Guest Ed., Special Issue: Image Understanding Research At The | university | Of Maryland |
| Guest Eds., Special Issue: Computer Vision Research At The | university | Of Southern California |
| Guest Eds., Special Issue: Machine Vision Research At Osaka | university | |
| Image And Data Analysis: The Multiscale Approach, Cambridge | university | Press, Cambridge |
| Image Understanding And Robotics Research At Columbia | university | |
| Image Understanding And Robotics Research At Columbia | university | |
| Image Understanding And Robotics Research At Columbia | university | |
| Image Understanding And Robotics Research At Columbia | university | |
| Image Understanding At Cornell | university | |
| Image Understanding At The | university | Of Rochester |
| Image Understanding At The | university | Of Rochester |
| Image Understanding Research At Brown | university | |
| Image Understanding Research At Colorado State | university | |
| Image Understanding Research At Columbia | university | |
| Image Understanding Research At Columbia | university | |
| Image Understanding Research At The | university | Of Maryland (December 1986 - January 1988) |
| Image Understanding Research At The | university | Of Maryland (January 1988-February 1989) |
| Image Understanding Research At The | university | Of Maryland: Video Surveillance And Tracking |
| Image Understanding Research At The | university | Of Utah |
| Image Understanding Research At | university | Of Washington |
| Image Understanding Research For Battle,Eld Awareness At Johns Hopkins | university | |
| Image Understanding Research For Battlefield Awareness At Johns Hopkins | university | |
| Images And Understanding, Cambridge | university | Press, Cambridge |
| In The Eye Of The Beholder: The Science Of Face Perception, Oxford | university | Press |
| Intelligent Systems-Concepts And Applications (Festschrift Honoring Prof. Yoh-Han Pao, Published In Connection With A Meeting Held At Case Western Reserve | university | , Cleveland, Oh, May 20, 1993), Plenum |
| International Conference On Parallel Processing, | university | Park, Pa |
| International Workshop On Graphics Recognition, | university | Park, Pa |
| Iu At The | university | Of Utah: Building 3-D Models From Sensed Data |
| Iu At The | university | Of Utah: Extraction Of Micro-Terrain Features |
| Linking Psychophysics, Neurophysiology, And Computational Vision (Abstracts Of Papers Presented At Rutgers | university | , New Brunswick, Nj, In Celebration Of The 65th Birthday Of Bela Julesz, April 30 - May 1, 1993) |
| Machine Intelligence 13|Machine Intelligence And Inductive Learning, Oxford | university | Press |
| Machine Intelligence 14|Applied Machine Intelligence, Oxford | university | Press |
| Mathematical Foundations Of Computer Graphics, Cambridge | university | Press, Cambridge |
| Mathematics Of Surfaces Iii (Oxford, Uk, September 1988), Oxford | university | Press, Oxford, The |
| Mental Imagery: On The Limits Of Cognitive Science, Yale | university | Press, New Haven |
| Morphometric Tools For Landmark Data, Cambridge | university | Press, Cambridge |
| Multidisciplinary Image Understanding Research At The | university | Of Maryland |
| Multiple Image Analysis At The Hebrew | university | : Motion, Structure, And Recognition |
| Neural Networks For Pattern Recognition, Oxford | university | Press, Oxford |
| Object Recognition Through Invariant Indexing, Oxford | university | Press, Oxford |
| Overview Of Architecture Research For Image Understanding At The | university | Of Massachusetts, An |
| Overview Of The Computer Vision And Robotics Programme At The | university | Of Utah |
| Pattern Matching Algorithms, Oxford | university | Press |
| Pattern Recognition Using Neural Networks|Theory And Algorithms For Engineers And Scientists, Oxford | university | Press |
| Picture Theory-Essays On Verbal And Visual Representation, | university | Of Chicago Press, Chicago |
| Principal Investigator Report: Automated Vision And Sensing Systems At Boston | university | |
| Principal Investigator Report: Automated Vision And Sensing Systems At Boston | university | |
| Processing The Facial Image (Proceedings Of A Royal Society Discussion Meeting, July 9-10, 1991; Philosophical Transactions Of The Royal Society), Oxford | university | Press, Oxford |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Computer Vision At The | university | Of Massachusetts |
| Progress In Image Understanding At Brown | university | |
| Progress In Image Understanding At The | university | Of Rochester |
| Progress On Target And Terrain Recognition Research At Colorado State | university | |
| Progress On Vision Through Learning At George Mason | university | |
| Progress On Vision Through Learning: A Collaborative Effort Of George Mason | university | And [The] University Of Maryland |
| Progress On Vision Through Learning: A Collaborative Effort Of George Mason | university | And [The] University Of Maryland |
| Representations Of Vision-Trends And Tacit Assumptions About Vision Research, Cambridge | university | Press, Cambridge |
| Research At Brown | university | |
| Results And Problems In Combinatorial Geometry, Cambridge | university | Press, Cambridge |
| Robust Video Motion Detection And Event Recognition, Iuw, 51-54. 67. C.R. Dyer, Image-Based Scene Rendering And Manipulation Research At The | university | Of Wisconsin |
| Simulating Humans-Computer Graphics, Animation, And Control, Oxford | university | Press, Oxford |
| Small Sample Behavior Of Multi-Layer Feedforward Network Classifiers: Theoretical And Practical Aspects, Delft | university | Press, Delft |
| Spatial Vision In Humans And Robots (Toronto, Ontario, Canada, June 19-22, 1991), Cambridge | university | Press, Cambridge |
| Spatial Vision, Oxford | university | Press, Oxford |
| Summary Of Image Understanding Research At The | university | Of Massachusetts |
| Summary Of Progress In Image Understanding At The | university | Of Massachusetts |
| Symbolic Visual Learning, Oxford | university | Press |
| Symposium On Learning And Memory In Sensory Systems, Center For Visual Science, | university | Of Rochester, Rochester, Ny |
| Symposium On Localizing Visual Function In The Brain, Center For Visual Science, | university | Of Rochester, Rochester, Ny |
| Topology And Category Theory In Computer Science (Oxford Topology Symposium, Oxford, Uk, June 27-30, 1989), Oxford | university | Press |
| Vision: Coding And Efficiency, Cambridge | university | Press, Cambridge |
| Visual Pattern Analyzers, Oxford | university | Press, Oxford |
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| _ | unsupervised | _ |
| Adaptive Key Frame Extraction Using | unsupervised | Clustering |
| Adaptive Mixture Estimation And | unsupervised | Local Bayesian Image Segmentation |
| Bayesian Clustering For | unsupervised | Estimation Of Surface And Texture Models |
| Cluster Validation For | unsupervised | Stochastic Model-Based Image Segmentation |
| Cluster Validation For | unsupervised | Stochastic Model-Based Image Segmentation |
| Constraint Directed Learning For | unsupervised | Image Sequence Segmentation |
| Estimation Of Fuzzy Gaussian Mixture And | unsupervised | Statistical Image Segmentation |
| Estimation Of Generalized Multisensor Hidden Markov Chains And | unsupervised | Image Segmentation |
| Face Recognition Using A Hybrid Supervised/ | unsupervised | Neural Network |
| Face Recognition Using A Hybrid Supervised/ | unsupervised | Neural Network |
| Feature Reduction And | unsupervised | Classification Algorithm For Multispectral Data, A |
| Gibbs Random Fields, Fuzzy Clustering, And The | unsupervised | Segmentation Of Textured Images |
| Hidden Markov Fields And | unsupervised | Segmentation Of Images |
| Local Cross-Modality Image Alignment Using | unsupervised | Learning |
| Markov Random Field Model-Based Approach To | unsupervised | Texture Segmentation Using Local And Global Spatial Statistics, A |
| Markov Random Field Models For | unsupervised | Segmentation Of Textured Color Images |
| Maximum Likelihood | unsupervised | Textured Image Segmentation |
| Maximum-Likelihood Parameter Estimation For | unsupervised | Stochastic Model-Based Image Segmentation |
| Mrf Model-Based Method For | unsupervised | Textured Image Segmentation, An |
| Multiresolution Em Algorithm For | unsupervised | Image Classification, A |
| Multiscale Annealing For Real-Time | unsupervised | Texture Segmentation |
| Mutual Learning Of | unsupervised | Interactions Between Mobile Robots |
| N-Folded Symmetries By Complex Moments In Gabor Space And Their Application To | unsupervised | Texture Segmentation |
| Neural Network Based Scheme For | unsupervised | Video Object Segmentation, A |
| Non-Parametric Similarity Measures For | unsupervised | Texture Segmentation And Image Retrieval |
| Optimization Approach To | unsupervised | Hierarchical Texture Segmentation, An |
| Texture Synthesis And | unsupervised | Recognition With A Nonparametric Multiscale Markov Random Field Model |
| Toward The | unsupervised | Interpretation Of Outdoor Imagery |
| unsupervised | Bayesian Estimation For Segmenting Textured Images |
| unsupervised | Bayesian Model-Learning With Application To Textured And Polynomial Image Segmentation |
| unsupervised | Contour Estimation |
| unsupervised | Detection Of Straight Lines Through Possibilistic Clustering |
| unsupervised | Feature Reduction In Image Segmentation By Local Karhunan-Loeve Transform |
| unsupervised | Feature Reduction In Image Segmentation By Local Transforms |
| unsupervised | Image Segmentation Based On A Self-Organizing Feature Map And A Texture Measure |
| unsupervised | Image Segmentation Based On The Comparison Of Local And Regional Histograms |
| unsupervised | Image Segmentation Using A Distributed Genetic Algorithm |
| unsupervised | Image Segmentation Using An Unlabeled Region Process |
| unsupervised | Image Segmentation Using The Minimum Description Length Principle |
| unsupervised | Image Segmentation Using The Modified Pyramidal Linking Approach |
| unsupervised | Learning Of Hand-Printed Characters With Linguistic Information, An |
| unsupervised | Model-Based Object Recognition By Parameter Estimation Of Hierarchical Mixtures |
| unsupervised | Multiresolution Texture Segmentation Using Wavelet Decomposition |
| unsupervised | Multistage Segmentation Using Markov Random Field And Maximum Entropy Principle |
| unsupervised | Parallel Image Classificiation Using A Hierarchical Markovian Model |
| unsupervised | Regions Segmentation: Real Time Control Of An Upkeep Machine Of Natural Spaces |
| unsupervised | Segmentation Based On Multi-Resolution Analysis, Robust Statistics And Majority Game Theory |
| unsupervised | Segmentation Based On Multi-Resolution Analysis, Robust Statistics And Majority Game Theory |
| unsupervised | Segmentation Based On Robust Estimation And Cooccurrence Data |
| unsupervised | Segmentation By Use Of A Texture Gradient |
| unsupervised | Segmentation Of Color Images |
| unsupervised | Segmentation Of Gray Level Markov Model Textures With Hierarchical Self Organizing Maps |
| unsupervised | Segmentation Of Markov Random Field Modeled Textured Images Using Selectionist Relaxation |
| unsupervised | Segmentation Of Multisensor Images Using Generalized Hidden Markov Chains |
| unsupervised | Segmentation Of Noisy And Textured Images Using Markov Random Fields |
| unsupervised | Segmentation Of Textured Color Images Using Markov Random Field Models |
| unsupervised | Segmentation Of Textured Image Using Markov Random Field In Random Spatial Interaction |
| unsupervised | Segmentation Of Textured Images |
| unsupervised | Segmentation Of Textured Images By Edge Detection In Multidimensional Features |
| unsupervised | Segmentation Of Textured Images By Pairwise Data Clustering |
| unsupervised | Texture Based Image Segmentation By Simulated Annealing Using Markov Random Field And Potts Models |
| unsupervised | Texture Classification Using Vector Quantization And Deterministic Relaxation Neural Network |
| unsupervised | Texture Segmentation Algorithm With Feature Space Reduction And Knowledge Feedback, An |
| unsupervised | Texture Segmentation By Hebbian Learnt Cortical Cells |
| unsupervised | Texture Segmentation For Multispectral Remote-Sensing Images |
| unsupervised | Texture Segmentation Of Images Using Tuned Matched Gabor Filters |
| unsupervised | Texture Segmentation Using Gabor Filters |
| unsupervised | Texture Segmentation Using Markov Random Field Models |
| unsupervised | Texture Segmentation Using Multichannel Decomposition And Hidden Markov Models |
| unsupervised | Texture Segmentation Using Selectionist Relaxation |
| unsupervised | Texture Segmentation Using Stochastic Version Of The Em Algorithm And Data Fusion |
| unsupervised | Texture Segmentation Using Tuned Filters In Gaborian Space |
| unsupervised | Texture Segmentation Via Wavelet Transform |
| unsupervised | Textured Classification Of Images Using The Texture Spectrum |
| unsupervised | Textured Image Segmentation Using Feature Smoothing And Probabilistic Relaxation Techniques |
| Wold Features For | unsupervised | Texture Segmentation |
| X. Yu) And J. Yla-Jaaski, | unsupervised | Texture Segmentation Based On The Modified Markov Random Field Model |
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