Overview
- 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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Knowledge Transfer from Text Mining to Computer Vision
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Knowledge Transfer from Computer Vision to Text Mining
Keywords
About this book
Authors and Affiliations
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