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Abdollah Amirkhani
Also published under:A. Amirkhani
Affiliation
School of Automotive Engineering, Iran University of Science and Technology, Tehran, Iran
Topic
Neural Network,Bounding Box,Control Signal,Convolutional Neural Network,Estimation Error,External Disturbances,Fuzzy Logic,Fuzzy Neural Network,Object Detection,Optimization Algorithm,Sliding Mode Control,Adaptive Control,Adaptive Rule,Analytical Tools,Ant Colony Optimization,Artificial Intelligence Algorithms,Asymptotically Stable,Attention Mechanism,Autonomous Vehicles,Background Image,Background Subtraction,Background Subtraction Method,Batch Normalization Layer,Braking Force,Brand Name,CCTV Cameras,Car Model,Classification Process,Client-side,Common Datasets,Comparison Of Numerical Results,Control Parameters,Control Performance,Coronavirus,Cost Function,Curriculum Learning,Deep Convolutional Neural Network,Deep Learning,Deep Learning Techniques,Deep Network,Domain Adaptation,Domain Adaptive Object Detection,Domain Alignment,Domain Shift,Effect Of Uncertainty,Electric Power Steering,Electrical Engineering,Energy Values,Energy-based Model,Ensemble Model,
Biography
Abdollah Amirkhani received the MSc and PhD degrees (with honors) in electrical engineering from the Iran University of Science and Technology (IUST), Tehran, in 2012 and 2017, respectively. He earned the Outstanding Student Award (2015) from the First Vice President of Iran. In 2016, he received an award by the Ministry of Science, Research and Technology. He has been actively involved in several National R&D projects, related to the development of new methodologies and learning algorithms based on AI techniques. He is currently a lecturer in the School of Computer Engineering at IUST. His research interests include soft computing, fuzzy cognitive maps, data mining, and machine learning. He is a student member of the IEEE.