Authors:
- Provides a novel perspective on image analysis and text processing, presenting the scientific justification for treating the two disciplines in a similar manner
- Offers open source code for the techniques in the book at an associated website
- Reviews state-of-the-art similarity-based learning approaches, including nearest neighbor models, kernel methods and clustering algorithms
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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Table of contents (10 chapters)
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Front Matter
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Knowledge Transfer from Text Mining to Computer Vision
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Front Matter
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Knowledge Transfer from Computer Vision to Text Mining
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Faculty of Math. and Computer Science, University of Bucharest, Bucharest, Romania
Radu Tudor Ionescu
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Department of Computer Science, University of Bucharest, Bucharest, Romania
Marius Popescu
About the authors
Dr. Marius Popescu is an Associate Professor at the same institution.
Bibliographic Information
Book Title: Knowledge Transfer between Computer Vision and Text Mining
Book Subtitle: Similarity-based Learning Approaches
Authors: Radu Tudor Ionescu, Marius Popescu
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-3-319-30367-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-30365-9Published: 09 May 2016
Softcover ISBN: 978-3-319-80791-1Published: 27 May 2018
eBook ISBN: 978-3-319-30367-3Published: 25 April 2016
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: XXIV, 250
Number of Illustrations: 9 b/w illustrations, 33 illustrations in colour
Topics: Artificial Intelligence, Image Processing and Computer Vision, Data Mining and Knowledge Discovery