Keywords l

LADAR Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Laser Sensors for Range, Time of Flight (H3)
Section: LIDAR, LADAR -- Range data (H2)
* Model-Based Automatic Target Recognition (ATR) System for Forward-Looking Groundbased and Airborne Imaging Laser Radars (Ladar)

LAI Section: LAI, Leaf Area Index, Land Cover Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Lake Ice Detection Section: Lake and River Ice Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Lake Level Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Reservoir Monitoring, Reservoir Usage, Water Level, Lake Level (H2)

Land Cover Section: Changes using Landsat Images (H4)
Section: Global-Scale Analysis, Global Land Cover Analysis (H2)
Section: Land Cover Analysis, Specific Location Applications, Site Analysis, Site Specific (H1)
Section: Land Cover Analysis, Specific Site North America (H2)
Section: Land Cover Analysis, Specific Site, China (H2)
Section: Land Cover Analysis, Water Detection, Water Areas, Water Body (H1)
Section: Land Cover Change Analysis Using Learning, Neural Nets (H3)
Section: Land Cover Change Analysis, Remote Sensing Change Analysis, Temporal Analysis (H2)
Section: Land Cover, General Problems, Remote Sensing (H1)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Water Detection Using SAR (H2)
11 for Land Cover

Land Cover, Urban Section: Classification for Urban Area Land Cover, Remote Sensing (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Land Degradation Section: Land Degradation (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Land Mines Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Ground Penetrating Radar, UXO, Landmines, Explosives (H4)
* Polarimetric processing of coherent random noise radar data for buried object detection
* Ultrawideband Radar Images of the Surface Disturbance Produced by a Submerged, Mine-Like Object

Land Use Change Section: Land Use Change Analysis (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Land Use Section: Land Use Change Analysis (H3)
Section: Land Use, General Problems (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Landfill Site Section: Landfill Sites, Site Selection, Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Landform Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landform Analysis, Landform Description (H3)

Landing Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Aircraft Landings, Spacecraft Landing (H4)

Landmark Detection Section: Anotomical Landmark Detection, Landmark Location in Various Sensors (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Landmark Location Section: Anotomical Landmark Detection, Landmark Location in Various Sensors (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Landmarks Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Face Analysis, Facial Landmarks (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Localization, Georeference, Urban Regions, City Models, Building Models (H4)
Section: Navigation, Landmarks (H3)
Section: Qualitative Navigation, Drop Off, Where in the World or Region (H4)
* Visual Navigation for a Mobile Robot Using Landmarks
7 for Landmarks

Landmines Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Ground Penetrating Radar, UXO, Landmines, Explosives (H4)

LandSat Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Changes using Landsat Images (H4)
Section: Fusion of LANDSAT or Sentinel Images (H4)
Section: Land Surface Temperature using LandSat (H3)
Section: Radiometric Calibration of LandSat Scanners, Images, Cross-Calibration (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
7 for LandSat

Landsat, History Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Landsat Program: Recent History and Prospects, The
* Science of Landsat Analysis Ready Data

Landslide Laser Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, LiDAR, Laser Scanner (H4)

Landslide LiDAR Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, LiDAR, Laser Scanner (H4)

Landslide Risk Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Susceptibility, Landslide Risk Analysis, Hazards (H4)

Landslide SAR Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, SAR, InSAR, IFSAR, Radar (H4)

Landslide Susceptibility Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, Earthquake Related, Seismic Analysis (H4)
Section: Landslide Susceptibility, Landslide Risk Analysis, Hazards (H4)

Landslide Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Detection, Analysis, Damage Assessment, Deformations (H3)
Section: Specific Site Landslide Analysis (H4)

Landslides Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, Earthquake Related, Seismic Analysis (H4)

Lane Changing Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Changing, Lane-Change, Analysis, Control (H4)

Lane Departure Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance, Lateral Control (H4)

Lane Detection Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance, Lateral Control (H4)
Section: Lane Detection, Lane Following, White Line Detection (H3)

Lane Following Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance, Lateral Control (H4)
Section: Lane Detection, Lane Following, White Line Detection (H3)

Lane Keeping Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance, Lateral Control (H4)

Lane Markings Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Road Marking Detection, Visible, LiDAR (H3)

Language Analysis Section: Authorship Issues (H4)
Section: Grammar Based Analysis, Language Issues, Natural Language (H3)
Section: Language Translation, Grammar Based Analysis (H4)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Social Medial Processing (H4)
Section: Steganalysis for Text, Documents (H3)
7 for Language Analysis

Language Recognition Section: Language Recognition, Multi-Language Documents (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Language Vision Model Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Vision-Language Models, Language-Vision Models, VQA (H4)

Laparoscopy Section: Laparoscopy, Surgery (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Large-Scale Stereo Section: Large Scale Multi-View Stereo, Internet Scale, Many Views (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)

Large Baseline Stereo Section: Matching for Stereo, Wide Baseline Matching Issues (H3)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)

Large Displacement Flow Section: Large Displacement Optical Flow (H2)
Section: Optical Flow Field Computations and Use (H)

Large Scale Database Section: Image Databases, Large Scale Systems, Web-Scale System (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Large Scale Systems, Web-Scale System, Learning, Neural Nets (H4)

Laser Range Finders Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Laser Sensors for Range, Time of Flight (H3)

Laser Scanner Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Road Following, Depth, Stereo Based, Off-Road, Safe Path (H3)

Laser Scanners Section: Buildings from Depth Data, LiDAR Data (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)

Laser Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Forest Analysis, Terrestrial Laser Scanner, Terrestrial LiDAR, TLS (H4)
Section: Shape from Laser Ranging and Structured Light Images (H1)

LASSO Regression Section: Group LASSO, Trace LASSO (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Latent Fingerprints Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Latnet Fingerprint Recognition, Analysis (H3)

Lava Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Lava Flows, Eruptions Volcanoes, Thermal (H4)
Section: Monioring Mt. Etna (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Layout Analysis Section: Document Layout, Document Segmentation, Page Layout, Structure Analysis (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Layout to Image Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Text to Image, Layout to Image, Image Based Rendering (H3)

Layout Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Room Layout (H4)

LBP Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Analysis, Local Binary Patters for Face Recognition (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Local Binary Patterns, LBP, Point Features (H3)
Section: Local Binary Patterns, LPB for Texture (H3)
Section: Local Features, LBP, Patterns, for Pedestrian Detection, People Detection (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
7 for LBP

LDA Definition:* Linear Discriminant Analysis.
Section: Discriminant Analysis (H3)
Section: Invariants -- Linear Discriminant Analysis, Fisher Linear Discriminant (H3)
Section: LDA in Face Recognition (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Leaf Area Index Section: LAI, Leaf Area Index, Land Cover Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Leaf Nitrogen Section: Leaf Nitrogen, Crop Nitrogen (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Leaf Shape Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Plants, Leaf Shapes, Leaf Analysis, Leaf Segmentation (H4)

Learning Models Section: Learning Model Descriptions (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Learning Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Contrastive Learning (H2)
Section: Convolutional Neural Networks for Human Action Recognition and Detection (H4)
Section: Data Hiding, Steganography, Adversarial Networks, Convolutional Networks, Deep Learning (H3)
Section: Deep Networks, Deep Learning for Human Action Recognition (H4)
Section: Deep Neural Networks, Deep Learning for Super Resolution (H4)
Section: Domain Adaption, Cross-Domain, Learning, Re-Identification Issues (H4)
Section: Emotion Recognition, Deep Learning (H4)
Section: Evaluation and Analysis of Learning Techniques (H2)
Section: Face Expression Recognition Using Learning, Neural Nets (H4)
Section: Face Recognition Systems Using Neural Networks, Learning (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Generative Adversarial Network, Neural Networks for Super Resolution (H3)
Section: Human Posture, or Human Pose, Learning, Neural Networks (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Incremental Learning for Human Action Recognition (H4)
Section: Inpainting, GAN, CNN, Neural Nets, Learning (H4)
Section: Land Cover Change Analysis Using Learning, Neural Nets (H3)
Section: Large Scale Systems, Web-Scale System, Learning, Neural Nets (H4)
Section: Learning -- Conference Listing (H2)
Section: Learning Face Detection, Neural Nets, SVM (H3)
Section: Learning for Detecting Anomalies (H4)
Section: Learning for High Dynamic Range Generation (H4)
Section: Learning for Image Quality Evaluation, CNN, GAN (H3)
Section: Learning for Principal Components, Eigen Representations (H3)
Section: Learning for Super Resolution (H3)
Section: Learning in Computer Vision (H1)
Section: Learning in Computer Vision (H3)
Section: Learning Object Descriptions, Object Recognition (H2)
Section: Learning, General Non-Vision Learning Issues (H2)
Section: Learning, General Surveys, Overviews (H2)
Section: Learning, Neural Nets for Coding, Compression in Video (H2)
Section: Learning, Neural Nets for Human Detection, People Detection, Pedestrians (H4)
Section: Learning, Neural Networks for Single Image Super Resolution (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Meta-Learning (H3)
Section: Models, Inference, Learning Human Activities, Human Behavior (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Motion Segmentation, Neural Networks, Learning (H3)
Section: Multi-Object Tracking, Neural Networks, Learning (H4)
Section: Multiple Instance Learning (H2)
Section: Neural Network Guided Background Subtraction, Learning Methods (H4)
Section: Neural Networks and Learning for Human Action Recognition and Detection (H4)
Section: Neural Networks for Noise Removal, Denoising, Restoration (H2)
Section: Neural Networks, Learning for Image Compression (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Opeical Flow, Learning, Neural Networks, GAN (H2)
Section: Optical Flow Field Computations and Use (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Perceptual Grouping, Saliency, Neural Networks, Learning (H3)
Section: Privacy in Learning (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Self-Supervised Learning for Object Detection and Segmentation (H2)
Section: Self-Supervised Learning (H2)
Section: Single View 3D Reconstruction, Learning (H3)
Section: Tracking People, Re-Identification Issues, Learning (H4)
Section: Tracking using Neural Nets, Learning (H3)
Section: Unbalanced Datasets, Imbalanced Sample Sizes, Imbalanced Data, Long-Tailed Data (H3)
* Face Recognition with Learning Machines
* Hidden Tree Markov Models for Document Image Classification
* Learning Structural Descriptions from Examples
* Learning Texture-Discrimination Masks
* Optimizing Learning in Image Retrieval
* RIEVL: Recursive Induction Learning in Hand Gesture Recognition
* Some Experiments in Applying Inductive Inference Principles to Surface Reconstruction
71 for Learning

Least Median Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Least Median of Squares Based Robust Analysis of Image Structure

Least Significant Bit Section: Data Hiding, Steganography, LSB, Least Significant Bit (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Least Squares Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Least Squares Applied to Restoration (H2)
* Sequential Coordinate-Wise Algorithm for the Non-negative Least Squares Problem

Left Luggage Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Unattended Package, Abandoned Luggage, Left Luggage, Theft (H4)

Left Ventricle Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Deformable Models, Cardiac Motion Models for Volumes, Left Ventricle (H3)

Legged Locomotion Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Legged Locomotion Robots, Assistants (H3)

Lens Distortion Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters (H2)
* Calibration of Stereo Cameras Using a Non-Linear Distortion Model
* Efficient and Accurate Camera Calibration Technique for 3-D Machine Vision, An

Leukemia Section: Blood Cell Cancers, Lymphoma, Leukemia (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Leukocyte Section: Blood Cells, Counting, Extraction, Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Levee Monitoring Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Dam Analysis and Monitoring, Levee Analysis, Deformation, Erosion (H4)

Level Set Methods Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Optical Flow Field Computations and Use (H)
* Image-Processing: Flows under Min/Max Curvature and Mean-Curvature
* Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision and Materials Science

Level Set Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Level Set Models for Volumes (H3)
Section: Level Set Segmentation, Level Set Methods (H2)
Section: Level Sets, Medical Image Segmentation (H3)
Section: Level Sets, Shape Models, Prior Shape Models (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* new time dependent model based on level set motion for nonlinear deblurring and noise removal, A
8 for Level Set

Libraries Section: Document Retrieval Systems, Databases and Issues, Libraries (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)

License Plate Recognition Section: License Plate Recognition, Extraction, Analysis (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Large-scale privacy protection in Google Street View

License Plates Section: License Plate Recognition, Extraction, Analysis (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

LiDAR Calibration Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Calibration -- Laser Scanner Multi-Path, Multipath (H4)
Section: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Laser Scanner Calibration -- Calgary Group, Lichti (H4)
Section: RGB-D Laser Scanner Calibration, Color and LIDAR (H4)

Lidar Inpainting Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Inpainting, Inpainting Range Images, Range, Depth Data (H4)

LiDAR Odometry Section: LiDAR Odometry, Distance Measurments from LiDAR (H3)
Section: Optical Flow Field Computations and Use (H)

Lidar Registration Section: ICP, Iterative Closest Point Registeration for Point Clouds (H4)
Section: Register Point Cloud Data, Point Cloud Matching, Laser Scanner Data (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: RGB-D Registeration, RGBD Registraion, Color and LiDAR (H4)

LiDAR Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Biomass Measurements, Forest, LiDAR Techniques, Airborne Laser (H4)
Section: Biomass Measurements, Forest, Terrestial Laser Techniques, TLS (H4)
Section: Buildings from Depth Data, LiDAR Data (H2)
Section: Buildings from Terrestrial Laser Data, Mobile Scanners, Ground-Based LiDAR (H3)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Cultural Heritage Modeling Systems, Laser, LiDAR (H3)
Section: DEM, DSM, DTM, Generation Using LiDAR, LIDAR, Laser Data (H2)
Section: Denoising, Range Images, Range, Depth Data (H4)
Section: Forest Analysis, Canopy Heights, LiDAR (H4)
Section: Forest Analysis, Depth, LiDAR, Laser Scanner (H4)
Section: Fusion, Range or Depth and Intensity or Color Data (H3)
Section: Laser Sensors for Range, Time of Flight (H3)
Section: LiDAR for Aerosols, Aerosol Optical Depth, Air Quality (H4)
Section: LiDAR for Land Cover, Laser Scanners for Land Cover, Remote Sensing (H2)
Section: Localization, LiDAR, Laser, Depth, 3D Data, Range Based (H4)
Section: Obstacles, Objects on the Road Using Radar, Sonar, LiDAR, Active Vision (H4)
Section: Radiometric Calibration of Laser Scanners, LIDAR (H3)
Section: Range Data, Point Cloud Processing and Analysis (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Road Following, Depth, Stereo Based, Off-Road, Safe Path (H3)
Section: Road Marking Detection, Visible, LiDAR (H3)
25 for LiDAR

LiDAR, Roads Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Road Extraction in Radar, SAR, Lidar, Laser, Depth (H2)

Lie Groups Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Dominant-Subspace Invariants

Lifelog Section: Lifelog, Daily Activities (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Lifting Operator Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Wavelet Lifting Operator, Transform (H4)

Light Field Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Light Field Cameras, Images, and Analysis (H2)
Section: Light Field Compressed Sensing (H3)
Section: Light Field Depth Estimation (H3)
Section: Light Field Rendering (H4)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Super Resolution for Light Field Images and Data (H3)
8 for Light Field

Light Source Direction Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Light Source Detection, Light Source Estimation (H2)
Section: Light Source Direction Computations, Illumination Information, Illuminant (H3)
* Estimation of Illuminant Direction, Albedo, and Shape from Shading

Lightfield Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Light Field Cameras, Images, and Analysis (H2)

Lighting Model Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Lighting Effects, View Generation, Graphics Issues (H3)

Lighting Section: Face Analysis, Shading, Illumination, Lighting and Color Variations (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Lightness Section: Color Constancy, Retinex (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)

Lightning Section: Lightning Detection, Analysis (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Lightweight Super Resolution Section: Lightweight Super Resolution (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)

Line Adjacency Graph Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Run-Length Coding Representations and Operations (H2)

Line Approximation Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Generation of Straight Line Segments or Curve Partitions (H1)

Line Detection Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Hueckel -- Basis Functions, Model Fitting for Edge Detection (H2)
Section: Line Detectors, Direct Detection of Straight Lines (H2)
Section: Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
Section: Road Junctions, Road Intersections (H2)
Section: Road Network Detection, Road Extraction Systems (H1)
* Mathematical Models for Automatic Line Detection
8 for Line Detection

Line Drawings Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Creation of Line Drawings, Detection of Wireframes (H2)
Section: Shape from Line Drawings, Junction Labeling (H1)
Section: Surface and Shape from Contours or Silhouettes (H1)
* Extraction of the Line Drawing of 3-Dimensional Objects by Sequential Illumination from Several Directions

Line Drawings, Analysis Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Line Drawing Analysis, Wireframes (H2)

Line Drawings, Shape Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Creation of Line Drawings, Detection of Wireframes (H2)
Section: Shape from Line Drawing, Shape from Lines (H2)

Line Features Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Calibration Using Line Features, Lines (H3)

Line Following Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Detection, Lane Following, White Line Detection (H3)

Line Labeling Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Line Labeling Techniques (H2)
Section: Shape from Line Drawings, Junction Labeling (H1)

Line Labels Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Extracting a Valid Boundary Representation from a Segmented Range Image

Line Matching Section: 2-D Line Segments with 2-D Structure (H2)
Section: 2-D Lines with 3-D Structure (H2)
Section: 3-D Lines with 3-D Structure (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Line of Sight Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Visibility Analysis, Sight Lines, Line of Sight (H3)

Line Segments Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Generation of Straight Line Segments or Curve Partitions (H1)
Section: Line Detectors, Direct Detection of Straight Lines (H2)
* Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data, A

Line Vectorization Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Line Vectorization, Document Analysis (H2)

Linear Constraints Section: Optical Flow Field Computations and Use (H)
* Performance of Camera Translation Direction Estimators from Optical-flow: Analysis, Comparison, and Theoretical Limits, The

Linear Discriminant Analysis Section: Discriminant Analysis (H3)
Section: Invariants -- Linear Discriminant Analysis, Fisher Linear Discriminant (H3)
Section: LDA in Face Recognition (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Linear Embedding Section: Locally Linear Embedding, Nonlinear Embedding (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Linear Features Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Extended Linear Features - Beyond Segments (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Line Vectorization, Document Analysis (H2)
* Approach to the Recognition of Contours and Line-Shaped Objects, An

Linear Prediction Section: Linear Prediction Techniques (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Linear Programming Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Linear Programming Approach fo the Weighted Graph Matching Problem, A

Lines Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Digital Geometry -- Lines, Curves and Contours (H3)

Lines, Colinear Section: Colinear Line Segments (Collinear) (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Lines, General Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Systems for Lines and Curves (H2)

Linkoping Univ. * *Linkoping University

Lip Detection Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Mouth Location, Lip Location, Detection (H3)

Lip Reading Section: Combined Audio Visual Recognition and Analysis (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Lipreading, Lip Reading, Lip Tracking (H2)

Lipreading Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Lipreading, Lip Reading, Lip Tracking (H2)

Lithology Section: Geologic Mapping, Geology Analysis, Mineralogy, Fault Zones (H1)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Liveness Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Liveness Detection, Spoofing, Fingerprint Recognition (H3)
Section: Liveness Detection, Spoofing, Presentation Attack, Faces, Other Biometrics (H3)

Liver Disease Section: Liver Disease, Tomography, CAT Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Local Binary Patterns Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Analysis, Local Binary Patters for Face Recognition (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Local Binary Patterns, LBP, Point Features (H3)

Local Features Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Local Features, Computation, Analysis (H3)

Localization Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Action Localization, Action Localisation (H4)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Audio Source Separation, Source Localization, Direction of Arrival, DoA, Analysis (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Iris Detection, Segmentation and Localization Systems (H3)
Section: Localization, Georeference, Urban Regions, City Models, Building Models (H4)
Section: Localization, GPS Assisted, GNSS Assisted, Guidance System Assisted, Other Annotation (H4)
Section: Localization, LiDAR, Laser, Depth, 3D Data, Range Based (H4)
Section: Localization, RFID Tags (H4)
Section: Localization, Where is the robot, Where is the camera (H3)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Object Localization (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* more you learn, the less you store: Memory-controlled incremental SVM for visual place recognition, The
16 for Localization

Localization, Indoor Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Indoor Localization, Navigation Issues, Non-Image, Wi-Fi, Phone Positioning (H4)
Section: Indoor Navigation Issues, Lines, Walls, Doors, Flat Surfaces (H3)

Locally Linear Embedding Section: Locally Linear Embedding, Nonlinear Embedding (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Log-Polar Sensor Section: Optical Flow Field Computations and Use (H)
* On the Estimation of Depth from Motion Using an Anthropomorphic Visual Sensor

Log-Polar Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Complex Log Mapping, Algorithms and Sensors (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Optical Flow Field Computations and Use (H)
* Binocular Fusion Revisited Utilizing a Log-Polar Tessellation
* Direct Computation of the Focus of Expansion from Velocity Field Measurements
* Disparity Estimation on Log-Polar Images and Vergence Control
7 for Log-Polar

Log Mapping Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Complex Log Mapping, Algorithms and Sensors (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Optical Flow Field Computations and Use (H)
* Complex Logarithmic Mapping and the Focus of Expansion
* Direct Computation of the Focus of Expansion
* Direct Estimation of Time-to-Impact from Optical Flow
* Geometric invariance in space-variant vision systems: The exponential chirp transform
* Motion Stereo Using Ego-Motion Complex Logarithmic Mapping
* On the Advantage of Polar and Log-Polar Mapping for Direct Estimation of Time-to-Impact from Optical Flow
* Position, Rotation and Scale Invarient Optical Correlation
12 for Log Mapping

Log Polar Mapping Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Segmentation of Frame Sequence Obtained by a Moving Observer

Logo Recognition Section: Analysis of Graphics, Logos (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Analysis of Compressed Document Images for Dominant Skew, Multiple Skew, and Logotype Detection
* Applying Algebraic and Differential Invariants for Logo Recognition
* Neural Based Architecture for Spot-Noisy Logo Recognition, A
* Shape-Based Retrieval: A Case-Study with Trademark Image Databases
* Trademark Shapes Description by String-Matching Techniques
* Using Negative Shape Features for Logo Similarity Matching
9 for Logo Recognition

Logs Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Lumber, Logs, Wood (H3)

Long-Tailed Data Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Unbalanced Datasets, Imbalanced Sample Sizes, Imbalanced Data, Long-Tailed Data (H3)

Long Sequence Section: Long Sequence Matching and Motion (H2)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

Long Short-Term Memory Section: LSTM: Long Short-Term Memory for Captioning, Image Captioning (H3)
Section: LSTM: Long Short-Term Memory (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Longwave Radiation Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Upward Longwave Radiation, Outgoing Longwave Radiation, Upwelling Radiation (H4)

Loop Closure Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Loop Closure, Simultaneous Localization and Mapping (H3)

Loss Functions Section: Loss Functions, Triplet Loss Function, Deep Learning, Neural Netowrks (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Lossless Compression Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Lossless Coding, Lossless Compression, Transmission (H2)
* Lossless Compression of AVIRIS Images by Vector Quantization, The

Low-Rank Representation Section: Human Action Recognition, Sparse Techniques, Low-Rank, SVM (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Low Bit Rate Coding Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: High Rate Compression, Low Bit Rate Compression, Region Based Coding (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion Compensation, Block, Region, Object, and Low Bit Rate Coding (H2)
Section: Motion Compensation, Low Bit Rate, Survey, Evaluations (H4)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)

Low Dose CT Section: Few Views, Limited Views, Low Dose, Tomographic Image Reconstruction (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Low Light Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Low Light Enhancement (H3)
Section: Night Time Processing (H3)

Low Resolution Section: Face Recognition at a Distance, In the wild, In-the-Wild, Low Resolution Faces (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

LSB Section: Data Hiding, Steganography, LSB, Least Significant Bit (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

LSTM Section: LSTM: Long Short-Term Memory for Captioning, Image Captioning (H3)
Section: LSTM: Long Short-Term Memory (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Luggage Inspection Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Surveillance Systems, Applied to Baggage Inspection, Cargo Inspection (H3)

Lumber Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Lumber, Logs, Wood (H3)

Lunar Terrain Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Moon, Lunar Treeain, Lunar Analysis, Martian Terrain (H2)

Lunar Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Moon, Lunar Treeain, Lunar Analysis, Martian Terrain (H2)

Lung Cancer Section: Lungs, and Lung Cancer Image Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Lung Nodules Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pulmonary Nodules, Lung Nodules (H3)

Lungs Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Airway Tree Structure (H3)
Section: Bronchoscopy Systems, Bronchial Analysis (H3)
Section: Emphysema, Lung Analysis (H3)
Section: Lung Motion Analysis, Respiration, Breathing (H3)
Section: Lungs, and Lung Cancer Image Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pneumonia, Lung Analysis, Flu, COVID (H3)
Section: Pulmonary Nodules, Lung Nodules (H3)
Section: Thorax, Thoracic Analysis (H3)
* Rotation invariant features based on three dimensional Gaussian Markov random fields for volumetric texture classification
11 for Lungs

Lymph Nodes Section: Medical Applications -- Lymph Nodes (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Lymphoma Section: Blood Cell Cancers, Lymphoma, Leukemia (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Index for "m"


Last update:16-Mar-24 20:56:33
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