13 April 2018 Reinforcement learning in computer vision
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Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106961S (2018) https://doi.org/10.1117/12.2309945
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria
Nowadays, machine learning has become one of the basic technologies used in solving various computer vision tasks such as feature detection, image segmentation, object recognition and tracking. In many applications, various complex systems such as robots are equipped with visual sensors from which they learn state of surrounding environment by solving corresponding computer vision tasks. Solutions of these tasks are used for making decisions about possible future actions. It is not surprising that when solving computer vision tasks we should take into account special aspects of their subsequent application in model-based predictive control. Reinforcement learning is one of modern machine learning technologies in which learning is carried out through interaction with the environment. In recent years, Reinforcement learning has been used both for solving such applied tasks as processing and analysis of visual information, and for solving specific computer vision problems such as filtering, extracting image features, localizing objects in scenes, and many others. The paper describes shortly the Reinforcement learning technology and its use for solving computer vision problems.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. V. Bernstein, A. V. Bernstein, E. V. Burnaev, E. V. Burnaev, "Reinforcement learning in computer vision", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106961S (13 April 2018); doi: 10.1117/12.2309945; https://doi.org/10.1117/12.2309945


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