Image Retrieval and Classification in Relational Databases
Relational databases are used to store information in every kind of life and business. They are suited for storing structured data and binary large objects (BLOBs). Unfortunately, BLOBs and multimedia data are difficult to handle, index, query and retriev
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Rafał Scherer
Computer Vision Methods for Fast Image Classification and Retrieval
Studies in Computational Intelligence Volume 821
Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected]
The series “Studies in Computational Intelligence” (SCI) publishes new developments and advances in the various areas of computational intelligence—quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output. The books of this series are submitted to indexing to Web of Science, EI-Compendex, DBLP, SCOPUS, Google Scholar and Springerlink.
More information about this series at http://www.springer.com/series/7092
Rafał Scherer
Computer Vision Methods for Fast Image Classification and Retrieval
123
Rafał Scherer Institute of Computational Intelligence Częstochowa University of Technology Częstochowa, Poland
ISSN 1860-949X ISSN 1860-9503 (electronic) Studies in Computational Intelligence ISBN 978-3-030-12194-5 (hardcover) ISBN 978-3-030-12195-2 ISBN 978-3-030-12197-6 (softcover) https://doi.org/10.1007/978-3-030-12195-2
(eBook)
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