METU INFORMATICS INSTITUTE FRIDAY SEMINARS: DEEP LEARNING IN COMPUTER VISION

Deep Learning in Computer Vision
 Deep Neural Networks (DNNs) have been shown to achieve human-level accuracy for many vision tasks. On the other hand, they require considerable amounts of computational power and data to train. In this talk, I will first talk about the deep learning based approaches and their differences to traditional approaches. I will then give an overview of the deep learning ecosystem (tools and systems) for training and inference. Then I will be focusing on their application to the computer vision problems with a number of examples including image classification, object detection, image segmentation as well as generative models. I will then conclude by discussing the challenges and problems in current deep learning based approaches.
 Biography:
 Alptekin Temizel Assoc. Prof., Graduate School of Informatics, Middle East Technical University (METU) (2007-Current); B.Sc., Electrical and Electronics Engineering, METU (1999); Ph.D. Centre of Vision, Speech and Signal Processing, University of Surrey (2006). He co-founded Visioprime Ltd, UK, a company developing Intelligent Video Systems for Security, where he worked as senior research engineer in 2001-2006 and acquired a number of patents. He started as an Assistant Professor at METU in 2007 where he is currently an Associate Professor. He is the principal investigator of “GPU Education and Research Centre” and NVIDIA Deep Learning Institute Certified Instructor and University Ambassador. He collaborated with and advised several companies on video analytics, video surveillance systems/algorithms and GPU computing. He was a visiting researcher at Microsoft MLDC-Lisbon in the summers of 2014 and 2015. He was on sabbatical leave at University of Birmingham, UK in 2016-2017. He has been expert evaluator of EU H2020 and EUREKA research programs and nationally funded programs. His main research interests are video surveillance, computer vision, machine learning, deep learning, GPU programming and CUDA.

METU Informatics Institute Conference Room

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