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Machine Learning for Computer Vision

Machine Learning for Computer Vision

Cheston Tan, Joel Z. Leibo, Tomaso Poggio (auth.), Roberto Cipolla, Sebastiano Battiato, Giovanni Maria Farinella (eds.)
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Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry, and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University of Cambridge (Computer Vision and Robotics Group) and University of Catania (Image Processing Lab). Different topics are covered each year. A summary of the past Computer Vision Summer Schools can be found at: http://www.dmi.unict.it/icvss This edited volume contains a selection of articles covering some of the talks and tutorials held during the last editions of the school. The chapters provide an in-depth overview of challenging areas with key references to the existing literature.

년:
2013
판:
1
출판사:
Springer-Verlag Berlin Heidelberg
언어:
english
페이지:
250
ISBN 10:
3642286615
ISBN 13:
9783642286612
시리즈:
Studies in Computational Intelligence 411
파일:
PDF, 13.34 MB
IPFS:
CID , CID Blake2b
english, 2013
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Pravin Lal

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