Betka, A.[Abir]
* 2020: Grey wolf optimizer-based learning automata for solving block matching problem
Betke, M.[Margrit]
* 1995: Fast Object Recognition in Noisy Images Using Simulated Annealing
* 1995: Fast Object Recognition in Noisy Images Using Simulated Annealing
* 1996: Multiple Vehicle Detection and Tracking in Hard Real Time
* 1997: Information-Conserving Object Recognition
* 1998: Information-Conserving Object Recognition
* 1999: Gaze Detection Via Self-Organizing Gray-Scale Units
* 2000: Real-time multiple vehicle detection and tracking from a moving vehicle
* 2001: Communication via Eye Blinks: Detection and Duration Analysis in Real Time
* 2001: Necessary Conditions to Attain Performance Bounds on Structure and Motion Estimates of Rigid Objects
* 2001: Recognition, Resolution, and Complexity of Objects Subject to Affine Transformations
* 2002: Evaluation of tracking methods for human-computer interaction
* 2004: EyeKeys: A Real-Time Vision Interface Based on Gaze Detection from a Low-Grade Video Camera
* 2005: Fast Head Tilt Detection for Human-Computer Interaction
* 2005: Locally Switching Between Cost Functions in Iterative Non-rigid Registration
* 2005: MosaicShape: Stochastic Region Grouping with Shape Prior
* 2005: Tracking, analysis, and recognition of human gestures in video
* 2006: Detecting Instances of Shape Classes That Exhibit Variable Structure
* 2007: Block-Based MAP Disparity Estimation Under Alpha-Channel Constraints
* 2007: Tracking Large Variable Numbers of Objects in Clutter
* 2008: Detecting Objects of Variable Shape Structure With Hidden State Shape Models
* 2008: Human-Computer Interface Using Symmetry Between Eyes to Detect Gaze Direction, A
* 2008: Tracking with Dynamic Hidden-State Shape Models
* 2009: Tracking a Large Number of Objects from Multiple Views
* 2009: Tracking of cell populations to understand their spatio-temporal behavior in response to physical stimuli
* 2009: Tracking-reconstruction or reconstruction-tracking? Comparison of two multiple hypothesis tracking approaches to interpret 3D object motion from several camera views
* 2010: Information Fusion Approach for Multiview Feature Tracking, An
* 2011: Efficient track linking methods for track graphs using network-flow and set-cover techniques
* 2012: Cell morphology classification and clutter mitigation in phase-contrast microscopy images using machine learning
* 2012: Coupling detection and data association for multiple object tracking
* 2013: Online Motion Agreement Tracking
* 2013: Randomized Ensemble Tracking
* 2013: SAGE: An approach and implementation empowering quick and reliable quantitative analysis of segmentation quality
* 2014: 3D pose estimation of bats in the wild
* 2014: Thermal Infrared Video Benchmark for Visual Analysis, A
* 2015: How to Collect Segmentations for Biomedical Images? A Benchmark Evaluating the Performance of Experts, Crowdsourced Non-experts, and Algorithms
* 2015: Minimum Barrier Salient Object Detection at 80 FPS
* 2015: random forest approach to segmenting and classifying gestures, A
* 2015: Salient Object Subitizing
* 2015: Special issue on animal and insect behaviour understanding in image sequences
* 2016: Discovering useful parts for pose estimation in sparsely annotated datasets
* 2016: Global optimization for coupled detection and data association in multiple object tracking
* 2016: ICORD: Intelligent Collection of Redundant Data: A Dynamic System for Crowdsourcing Cell Segmentations Accurately and Efficiently
* 2016: Pull the Plug? Predicting If Computers or Humans Should Segment Images
* 2016: Unconstrained Salient Object Detection via Proposal Subset Optimization
* 2017: Comparing random forest approaches to segmenting and classifying gestures
* 2017: Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks
* 2017: Salient Object Subitizing
* 2018: Context-Sensitive Prediction of Facial Expressivity Using Multimodal Hierarchical Bayesian Neural Networks
* 2018: Making scanned Arabic documents machine accessible using an ensemble of SVM classifiers
* 2018: Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s)
* 2019: Home-Based Physical Therapy with an Interactive Computer Vision System
* 2019: Predicting How to Distribute Work Between Algorithms and Humans to Segment an Image Batch
* 2020: Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes
* 2020: method for detecting text of arbitrary shapes in natural scenes that improves text spotting, A
* 2020: Visual complexity analysis using deep intermediate-layer features
* 2021: Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System
* 2021: Semantic-Based Sentence Recognition in Images Using Bimodal Deep Learning
* 2021: Student Engagement Dataset
* 2022: Graph-Transformer for Whole Slide Image Classification, A
* 2022: Unified Framework for Domain Adaptive Pose Estimation, A
* 2023: Animal Pose Tracking: 3D Multimodal Dataset and Token-based Pose Optimization
* 2023: CDAC: Cross-domain Attention Consistency in Transformer for Domain Adaptive Semantic Segmentation
* 2023: Fusion Approaches to Predict Post-stroke Aphasia Severity from Multimodal Neuroimaging Data
Includes: Betke, M.[Margrit] Betke, M.
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