| _ | target | _ |
| A.1. | target | recognition |
| A.1. | target | recognition |
| Adaptive | target | Recognition Using Reinforcement Learning |
| Advances In Image Compression And Automatic | target | Recognition (Orlando, Fl, March 30-31 |
| Aided And Automatic | target | Recognition Based Upon Sensory Inputs From Image Forming Systems |
| Appearance-Based Automatic | target | Recognition In Overhead Ladar Range Imagery |
| Architecture, Hardware, And Forward-Looking Infrared Issues In Automatic | target | Recognition (Orlando, Fl, April 12-13 |
| Automatic Detection Of | target | s Against Cluttered Backgrounds Using A Fractal-Oriented Statistical Analysis And Radon Transform |
| Automatic | target | Detection And Recognition In Multiband Imagery: A Unified Ml Detection And Estimation |
| Automatic | target | Recognition By Matchingoriented Edge Pixels |
| Automatic | target | Recognition For Naval Traffic Control Using Neural Networks |
| Automatic | target | Recognition Organized Via Jump-Diffusion Algorithms |
| Automatic | target | Recognition Using A Feature-Decomposition And Data-Decomposition Modular Neural Network |
| Automatic | target | Recognition Vii Orlando, Fl, April 22-24 |
| Automatic | target | Recognition Viii (Orlando, Fl, April 13-17 |
| Automatic | target | Segmentation By Locally Adaptive Image Thresholding |
| C.6 | target | recognition |
| C.6. | target | recognition |
| C.6. | target | recognition |
| Camera Calibration Using 4 Point- | target | s, A |
| Characterizing Natural Backgrounds For | target | Detection |
| Combination Of Two Learning Algorithms For Automatic | target | Recognition |
| Comparing Features For | target | Tracking In Traffic Scenes |
| Context Dependent | target | Recognition |
| Context-Aided False Alarm Reduction For Sar Automatic | target | Recognition |
| Correspondence Analysis For | target | Tracking In Infrared Images |
| Data Structures And | target | Classification (Orlando, Fl, April 1-2 |
| Decentralized Bayesian Algorithm For Identification Of Tracked | target | s, A |
| Detecting Multiple Moving | target | s Using Deformable Contours |
| Detection And Remediation Technologies For Mines And Minelike | target | s (Orlando, Fl, April 9-12 |
| Detection And Remediation Technologies For Mines And Minelike | target | s Ii Orlando, Fl, April 22-24 |
| Detection And Remediation Technologies For Mines And Minelike | target | s Iii (Orlando, Fl, April 13-17 |
| Detection And Tracking Of Single-Pixel | target | s Based On Trajectory Continuity |
| Detection Of Mines And Minelike | target | s Using Principal Components And Neural-Network |
| Detection Techniques For Mines And Minelike | target | s (Orlando, Fl, April 17-21 |
| Digital Signal Processing, Association And Tracking Of Point Source, Small And Cluster | target | s (Orlando, Fl, March 27-29 |
| Dynamic Model Matching For | target | Recognition From A Mobile Platform |
| Dynamic Scene Analysis And Video | target | Tracking |
| Dynamic | target | Recognition System, A |
| Effective Regional Descriptor And Its Application To | target | Recognition, An |
| Estimating Squinted Sar Data: An Efficient Multivariate Minimization Approach Using Only Essential 3-D | target | Information |
| Experimental | target | Recognition System For Laser Radar Imagery, An |
| Fast Algorithm For | target | Shadow Removal In Monocular Colour Sequences, A |
| Feature Extraction Using Attributed Scattering Center Models For Model-Based Automatic | target | Recognition |
| Feature Extraction Using Attributed Scattering Center Models For Model-Based Automatic | target | Recognition |
| Flexible Histograms: A Multiresolution | target | Discrimination Model |
| Focus Of Attention (Foa) Identification From Compressed Video For Automatic | target | Recognition (At |
| Focused | target | Segmentation Paradigm, A |
| Foveal Automatic | target | Recognition Using A Multiresolution Neural Network |
| Foveal Automatic | target | Recognition Using A Neural Network |
| Foveating Fuzzy Scoring | target | Recognition System, A |
| Frequency Domain Algorithm For Multiframe Detection And Estimation Of Dim | target | s, A |
| Fuzzy Logic Rule-Based Automatic | target | Recognizer, A |
| Generating Image Filters For | target | Recognition By Genetic Learning |
| Ground | target | Modeling And Validation Conference, Houghton, Mi |
| Guest Eds., Special Issue On Automatic | target | Recognition |
| Guest Eds., Special Issue--Automatic | target | Recognition |
| Hierarchical Integration Of Sensor Data And Contextual Information For Automatic | target | Recognition |
| Honeywell Progress On Knowledge-Based Robust | target | Recognition And Tracking |
| Hybrid System For | target | Classification, A |
| Image Understanding Research For Automatic | target | Recognition |
| Improved Ssda Applied In | target | Tracking, An |
| Intelligent Tactical | target | Screener, An |
| Interactive | target | Recognition Using A Database-Retrieval Oriented Approach |
| Invariance In Moving | target | Detection |
| Invariant Histograms And Deformable Template Matching For Sar | target | Recognition |
| Knowledge-Based Approach To The Detection, Tracking And Classification Of | target | Formations In Intrared Image Sequences, A |
| Learning To Fixate On 3d | target | s With Uncalibrated Active Cameras |
| Managing Within-Class | target | Variability In Sar Imagery With A Target Decomposition Model |
| Managing Within-Class | target | Variability In Sar Imagery With A Target Decomposition Model |
| Method Of Estimating The | target | Position For An Image Tracking System Of Moving Targets, A |
| Method Of Estimating The | target | Position For An Image Tracking System Of Moving Targets, A |
| Mobile Robot Sonar For | target | Localization And Classification |
| Model Based Detection Of | target | s In Fopen Sar Images |
| Model-Based Automatic | target | Recognition (Atr) System For Forwardlooking Groundbased And Airborne Imaging Laser Radars (Lada |
| Model-Based Automatic | target | Recognition System For The Ugv/Rsta Ladar |
| Model-Based Automatic | target | Recognition System For The Ugv/Rsta Ladar: Status At Demo C |
| Model-Based Neural Network For | target | Detection In Sar Images |
| Model-Based | target | Recognition In Foliage Penetrating Sar Images |
| Model-Based | target | Recognition In Pulsed Ladar Imagery |
| Modeling Clutter And Context For | target | Detection In Infrared Images |
| Motion Analysis Of Isolated | target | s In Infared Image Sequences |
| Motion Analysis Of Isolated | target | s In Infrared Image Sequences |
| Moving | target | Classification And Tracking From Real-Time Video |
| Moving | target | Detection In Foliage Using Along Track Monopulse Synthetic Aperture Radar Imaging |
| Multi-Stage | target | Recognition Using Modular Vector Quantizers And Multilayer Perceptrons |
| Multiple Stochastic Models For Recognition Of Occluded | target | s In Sar Images |
| Multiresolution Detection Of Coherent Radar | target | s |
| Multiresolution Surface Feature Analysis For Automatic | target | Identification Based On Laser Radar Images |
| Multistrategy Learning Approach For | target | Model Recognition, Acquisition, And Refinement, A |
| Neural Clustering Approach For High Resolution Radar | target | Classification, A |
| Neural Network/Pyramid Architectures That Learn | target | Context |
| New Efficient And Direct Solution For Pose Estimation Using Quadrangular | target | s: Algorithms And Evaluation, A |
| On The Positioning Of Multisensor Imagery For Exploitation And | target | Recognition |
| Optimal Waveform Selection For Radar | target | Classification |
| Parametric Attributed Scattering Center Model For Sar Automatic | target | Recognition, A |
| Performance Modeling And Adaptive | target | Detection |
| Phased Array Imaging Of Moving | target | s With Randomized Beam Steering And Area Spotlighting |
| Planning And Selective Perception For | target | Retrieval |
| Point | target | Detection In Spatially Varying Clutter |
| Polarimetric Fusion For Synthetic Aperture Radar | target | Classification |
| Pose Estimation For Sar Automatic | target | Recognition |
| Precise Matching Of 3-D | target | Models To Multisensor Data |
| Probe Based Recognition Of | target | s In Infrared Images |
| Probe-Based Automatic | target | Recognition In Infrared Imagery |
| Progress On | target | And Terrain Recognition Research At Colorado State University |
| Progress On The Fast Adaptive | target | Detection Program |
| Qualitative Motion Detection And Tracking Of | target | s From A Mobile Platform |
| Qualitative Reasoning And Modeling For Robust | target | Tracking And Recognition From A Mobile Platform |
| Qualitative | target | Motion Detection And Tracking |
| Radar | target | Identification Using Spatial Matched Filters |
| Recognition Of Partially Occluded | target | Objects |
| Reconnaissance, Surveillance And | target | Acquisition Research For The Unmanned Ground Vehicle Program |
| Reinforcement Learning For Integrating Context With Clutter Models For | target | Detection |
| Renovated Algorithm For Extracting Moving | target | From Background In Real Time Video Tracking System, A |
| Representation Of Uncertainty In Spatial | target | Tracking |
| Representing Environment Through | target | -Guided Navigation |
| Robot Self-Location Using Visual Reasoning Relative To A Single | target | Object |
| Robust Automatic | target | Recognition Using A Localized Boundary Representation |
| Robust Detection Of Sar/Ir | target | s Via Invariance |
| Scenario-Based Engineering Process For Reconnaissance, Surveillance, And | target | Acquisition |
| Signal And Data Processing Of Small | target | s (Orlando, Fl, April 16-18 |
| Signal And Data Processing Of Small | target | s 1991 (Orlando, Fl, April 1-3 |
| Signal And Data Processing Of Small | target | s 1992 (Orlando, Fl, April 20-22 |
| Signal And Data Processing Of Small | target | s 1993 (Orlando, Fl, April 12-14 |
| Signal And Data Processing Of Small | target | s 1994 (Orlando, Fl, April 5-7 |
| Signal And Data Processing Of Small | target | s 1995 (San Diego, Ca, July 11-13 |
| Signal And Data Processing Of Small | target | s 1996 (Orlando, Fl, April 9-11 |
| Signal And Data Processing Of Small | target | s 1997 San Diego, Ca, July 29-31 |
| Signal And Data Processing Of Small | target | s 1998 (Orlando, Fl, April 14-16 |
| Signal Detection Theory Approach To The Multiple Parallel Moving | target | s Problem |
| Signal Processing, Sensor Fusion, And | target | Recognition (Orlando, Fl, April 20-22 |
| Signal Processing, Sensor Fusion, And | target | Recognition Ii (Orlando, Fl, April 12-14 |
| Signal Processing, Sensor Fusion, And | target | Recognition Iii (Orlando, Fl, April 4-6 |
| Signal Processing, Sensor Fusion, And | target | Recognition Iv (Orlando, Fl, April 17-19 |
| Signal Processing, Sensor Fusion, And | target | Recognition V (Orlando, Fl, April 8-10 |
| Signal Processing, Sensor Fusion, And | target | Recognition Vi Orlando, Fl, April 21-24 |
| Signal Processing, Sensor Fusion, And | target | Recognition Vii (Orlando, Fl, April 13-15 |
| Single-Pixel | target | Detection And Tracking System, A |
| Spacial And Temporal Mechanisms In | target | Cueing |
| Stability And Sensitivity Of Topographic Features For Sar | target | Characterization |
| Structural Classifier For Ship | target | s, A |
| Subspace Method For Maximum Likelihood | target | Detection, A |
| Summary Of Progress In Flir/Ladar Fusion For | target | Identification At Rockwell |
| Svd Approach To Multi-Camera-Multi- | target | 3-D Motion-Shape Analysis, An |
| target | Detection In Foveal Atr Systems |
| target | Detection In Uwb Sar Images Using Temporal Fusion |
| target | Detection Using Phase-Based Gabor Element Aggregation |
| target | Discrimination In Synthetic Aperture Radar Using Artificial Neural Networks |
| target | Identification Using Geometric Hashing And Flir/Ladar Fusion |
| target | Indexing In Sar Images Using Scattering Centers And The Hausdorff Distance |
| target | Recognition In A Cluttered Scene Using Mathematical Morphology |
| target | Recognition Using Multi-Scale Gabor Filters |
| target | Tracking And Range Estimation Using An Image Sequence |
| target | s And Backgrounds: Characterization And Representation (Orlando, Fl, April 17-19 |
| target | s And Backgrounds: Characterization And Representation Ii (Orlando, Fl, April 8-10 |
| target | s And Backgrounds: Characterization And Representation Iii Orlando, Fl, April 21-23 |
| target | s And Backgrounds: Characterization And Representation Iv (Orlando, Fl, April 13-15 |
| Template Matching Of Binary | target | s In Grey-Scale Images: A Nonparametric Approach |
| Tracking And Detection Of Moving Point | target | s In Noise Image Sequences By Local Maximum Likelihood |
| Tree Search Algorithm For | target | Detection In Image Sequences, A |
| Triple: A Multi-Strategy Machine Learning Approach To | target | Recognition |
| Unified, Multiresolution Framework For Automatic | target | Recognition, A |
| Unified, Multiresolution Framework For Automatic | target | Recognition, A |
| Use Of Context For False Alarm Reduction In Sar Automatic | target | Recognition |
| Using Centroid Covariance In | target | Recognition |
| Using Stereomotion To Track Binocular | target | s |
| Visual Tracking Of A Moving | target | By A Camera Mounted On A Robot: A Combination Of Control And Vision |
| Visualization And Verification Of Automatic | target | Recognition Results Using Combined Range And Optical Imagery |
| Wavelet-Based | target | Hashing For Automatic Target Recognition |
| Wavelet-Based | target | Hashing For Automatic Target Recognition |
| Workshop On Algorithm-Guided Parallel Architectures For Automatic | target | Recognition, Leesburg, Va |
172 for target
| _ | task | _ |
| Acronym Model Based Vision In The Intelligent | task | Automation Project |
| Acronym Model Based Vision In The Intelligent | task | Automation Project |
| Affine Coordinate Based Algorithm For Reprojecting The Human Face For Identification | task | s, An |
| Algorithm Database For An Image Understanding | task | Execution Environment, An |
| Analysis And Performance Of Two Middle-Level Vision | task | s On A Fine-Grained Simd Tree Machine, The |
| Applications Of Non-Metric Vision To Some Visual Guided | task | s |
| Automatic Sensor Placement From Vision | task | Requirements |
| Complexity Of Perceptual Search | task | s, The |
| Computational Methods For | task | -Directed Sensor Data Fusion And Planning |
| Computer-Vision | task | Distribution On A Multicluster Mimd System |
| Computing Swept Volumes For Sensor Planning | task | s |
| Coordinated Evaluation Of Parallel Architectures For Perceptual | task | s, The |
| Designing Stereo Heads Using | task | Domain Constraints |
| Devious: A Distributed Environment For Vision | task | s |
| Efficient Embedding Of Interprocessor Communications In Parallel Implementations Of Intermediate Level Vision | task | s |
| Efficient Use Of Parallelism In Intermediate Level Vision | task | s |
| Eye-In-Hand Robotic | task | s In Uncalibrated Environments |
| Formulation Of Parallel Image Processing | task | s |
| Frame-Based System For Modelling And Executing Visual | task | s, A |
| Framework For Implementing Multi-Sensor Robotic | task | s, A |
| Generating An Interpretation Tree From A Cad Model For 3d-Object Recognition In Bin-Picking | task | s |
| Global Optimization For Mapping Parallel Image Processing | task | s On Distributed Memory Machines |
| Guest Ed., Special Issue On Robotic Assembly And | task | Planning, Ai Magazine 11(1), Spring 1990 |
| Handey-A Robot | task | Planner, Mit Press, Cambridge |
| Integrating Vision And Touch For Object Recognition | task | s |
| Intelligent Operating System For Executing Image Understanding | task | s On A Reconfigurable Parallel Architecture, An |
| Learning By Watching: Extracting Reusable | task | Knowledge From Visual Observation Of Human Performance |
| Load Balancing Requirement In Parallel Implementations Of Image Feature Extraction | task | s |
| Low-Level Image Analysis | task | s On Fine-Grained Tree-Structured Simd Machines |
| Machine Vision For Industry: | task | s, Tools, And Techniques |
| Mapping Computer-Vision-Related | task | s Onto Reconfigurable Parallel-Processing Systems |
| Measuring The Effectiveness Of | task | -Level Parallelism For High-Level Vision |
| Methodology For Evaluation Of | task | Performance In Robotic Systems: A Case Study In Vision-Based Localization, A |
| Model For An Intelligent Operating System For Executing Image Understanding | task | s On A Reconfigurable Parallel Architecture, A |
| Model Generation Method For Object Recognition | task | By Pictorial Examples, A |
| Modeling Sensor Confidence For Sensor Integration | task | s |
| Monitoring An Assembly | task | By Perception Requests |
| Mvp Sensor Planning System For Robot Vision | task | s, The |
| Near-Minimum-Time | task | Planning For Fruit-Picking Robots |
| Neuromorphic Architecture For Cortical Multilayer Integration Of Early Visual | task | s, A |
| Non-Von'S Applicability To Three Ai | task | Areas |
| Novel Active-Vision-Based Visual-Threat-Cue For Autonomous Navigation | task | s |
| Objective Comparison Methodology Of Edge Detection Algorithms Using A Structure From Motion | task | , An |
| On Grasp Choice, Grasp Models, And The Design Of Hands For Manufacturing | task | s |
| On The Application Of Massively Parallel Simd Tree Machines To Certain Intermediate-Level Vision | task | s |
| On The Use Of Topological Constraints Within Object Recognition | task | s |
| Parallel Implementations Of Perceptual Grouping | task | s On Distributed Memory Machines |
| Path Planning For Mobile Manipulators For Multiple | task | Execution |
| Practical Pushing Planning For Rearrangement | task | s |
| Programming Intermediate Level Vision | task | s On Parallel Machines |
| Randomization For Robot | task | s: Using Dynamic Programming In The Space Of Knowledge States |
| Randomization In Robot | task | s |
| Real-Time Visual Sensing For | task | Planning In A Field Navigation Vehicle |
| Recognizing Assembly | task | s Using Face-Contact Relations |
| Recompiling A Geometrical Model Into An Interpretation Tree For Object Recognition In Bin-Packing | task | s |
| Robot System That Observes And Replicates Grasping | task | s, A |
| Robot | task | Programming By Human Demonstration |
| Simulation Of Object And Human Skin Deformations In A Grasping | task | |
| task | Driven 3d Object Recognition System Using Bayesian Networks, A |
| task | Driven Perceptual Organization For Extraction Of Rooftop Polygons |
| task | Frames In Robot Manipulation |
| task | Frames In Visuo-Motor Coordination |
| task | Frames: Primitives For Sensory-Motor Coordination |
| task | Oriented Vision |
| task | -Directed Computation Of Quantitative Decisions From Sensor Data |
| task | -Directed Evaluation Of Image Segmentation Methods |
| task | -Directed Sensor Fusion And Planning: A Computational Approach, Kluwer |
| task | -Level Planning Of Pick-And-Place Robot Motions |
| task | -Level Tour Plan Generation For Mobile Robots |
| task | -Oriented Generation Of Visual Sensing Strategies |
| task | -Oriented Generation Of Visual Sensing Strategies In Assembly Tasks |
| task | -Oriented Generation Of Visual Sensing Strategies In Assembly Tasks |
| task | -Oriented Optimal Grasping By Multifingered Robot Hands |
| task | -Relevant Relaxation Network For Visuo-Motor(Y) Systems |
| task | -Specific Gesture Analysis In Real Time Using Interpolated Views |
| task | -Specific Utility In A General Bayes Net Vision System |
| Toward An Assembly Plan From Observation-Part I: | task | Recognition With Polyhedral Objects |
| Toward Automatic Robot Instruction From Perception--Temporal Segmentation Of | task | s From Human Hand Motion |
| Towards An Assembly Plan From Observation: | task | Recognition With Polyhedral Objects |
| Uncalibrated Visual | task | s Via Linear Interaction |
| Vision-Based Fuzzy Controllers For Navigation | task | s |
| Visual Compliance: | task | -Directed Visual Servo Control |
| Visual Components Of An Automated Inspection | task | , The |
| Visual Control Of Grasping And Manipulation | task | s |
| Visual Space | task | Specification, Planning And Control |
85 for task