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Safwan Wshah
Affiliation
Department of Computer Science and Vermont Complex Systems Center, University of Vermont, Burlington, VT, USA
Topic
Deep Learning Models,Convolutional Neural Network,Deep Learning,Long Short-term Memory,Aerial Images,Anomaly Detection,Anomaly Score,Convolutional Neural Network Architecture,Deep Learning Approaches,F1 Score,Feature Aggregation,Generative Adversarial Networks,Image Ground,Multi-head Self-attention,Multivariate Time Series,Polar Transformation,Real-world Scenarios,Street View Images,Training Data,Wireless Sensor Networks,3D Convolution,3D Kernel,Above-mentioned Methods,Attention Mechanism,Autonomous Vehicles,Average Pooling Layer,B-type Natriuretic Peptide,Backbone Feature,Basic Architecture,Batch Size,Bayesian Inference,Benchmark,Bidirectional Long Short-term Memory,Breast Cancer Screening,Calibrated Model Parameters,Challenging Benchmark,Coastal Settings,Color Space,Complex Models,Compression Ratio,Convolutional Neural Network Model,Counterfactual,Cross-view Geo-localization,Cross-view Image,Current Algorithms,Data Augmentation,Data Streams,Deep Approach,Deep Fusion,Deep Models,
Biography
Safwan Wshah (Member, IEEE) received the Ph.D. degree in computer science and engineering from The State University of New York at Buffalo. He has a broad experience in deep learning, computer vision, data analytics, and image processing. He has received ten issued U.S. patents with four additional patents pending. He is the author of six journal publications and 23 conference proceedings. He has served on the organizing committee of top conferences and he serves as a reviewer/referee for several journals and conferences.