Items related to Machine Learning for Computer Vision
Synopsis
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.
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Review
From the reviews:
“This book should ... be of interest to anybody involved in computer vision or image and video analysis, as it presents many challenging scenarios to the machine learning community. ... this book presents a snapshot of key research in the areas of computer vision and machine learning. On this level, the book succeeds, with many first-class papers. I recommend the book to practitioners in the field, as well as those pursuing PhD-level studies.” (David Marshall, Computing Reviews, April, 2013)"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2012
- ISBN 10 3642286623
- ISBN 13 9783642286629
- BindingPaperback
- LanguageEnglish
- Number of pages274
- EditorCipolla Roberto, Battiato Sebastiano, Farinella Giovanni Maria
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