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Mårten Wadenbäck is an Associate Professor and Docent at Linköping University, specializing in computer vision and machine learning. His research explores advanced areas such as robust feature matching, neural descriptor analysis, and reinforcement learning. He has contributed to various noteworthy publications including 'Radially Distorted Homographies, Revisited' and 'DaD: Distilled Reinforcement Learning Diverse Keypoint Detection'. Mårten's works are widely recognized and presented at notable conferences like IEEE/CVF Conference on Computer Vision and Pattern Recognition. His academic trajectory is complemented by collaborative efforts with other professionals in the field, showcasing a strong commitment to advancing technology and methodologies in visual computing.
Linköping University • Linköping, Sweden
Associate Professorship in Computer Vision and Machine Learning.
Requirements are standardized across the Faculty of Science and Engineering (Institute of Technology) for international Master's programs.