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- Computing and Processing
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Amin Banitalebi-Dehkordi
Affiliation
Beauty Tech, Amazon
Topic
Batch Size,Consistency Regularization,Domain Adaptation,Generative Adversarial Networks,Graph Convolutional Network,Learning Algorithms,Object Detection,Pseudo Labels,Self-supervised Learning,Source Domain,Target Domain,Uniform Distribution,Unlabeled Data,Unlabeled Examples,Ablation,Absence Of Labels,Accurate Transfer,Affinity Score,Attention Mechanism,Augmented Version,Auxiliary Data,Auxiliary Dataset,Auxiliary Set,Baseline Methods,Batch Normalization Layer,Batch Of Images,Bounding Box,COCO Dataset,Candidate Solutions,Central Policy,Combinatorial Optimization Problem,Combinatorial Problem,Component Of Image,Convolutional Neural Network,Cross-entropy Loss,Curriculum Learning,Deep Q-network,Deep Reinforcement Learning,Distancing Measures,Distribution Of Categories,Domain Adaptation Methods,Domain Adaptive Object Detection,Domain Alignment,Domain Shift,Embedding Learning,Empirical Validation,Energy Values,Energy-based Model,Facial Components,Facility Location Problem,
Biography
Amin Banitalebi-Dehkordi received the Ph.D. degree in electrical and computer engineering from The University of British Columbia (UBC), Canada, in 2014. He is currently a Principal Researcher of machine learning and technical lead with the Vancouver Research Centre, Huawei Technologies Canada Company, Ltd. His academic career has resulted in publications in the fields of computer vision and pattern recognition, visual attention modeling, video quality assessment, and high dynamic range video. His industrial experience expands to areas in machine learning, deep learning, computer vision, NLP, and signal/image/video processing.