Overview
- Provides a rare opportunity to gain an overview of relevant, supportive, inter-disciplinary and innovative research and technical works on Big Data in Marine Biology in one place
- This book is also a useful reference book for researchers and practitioners who are interested in handling big data that may be gathered from the Web or the natural world
- Includes various software components which are provided under open-source licenses that interested readers can potentially re-use for their own purposes
- The user interface developed will also be available, enabling readers to investigate their own marine biology questions
- Includes supplementary material: sn.pub/extras
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 104)
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Table of contents (18 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and tracking, fish species recognition and analysis, a large SQL database to record the results and an efficient retrieval mechanism. Novel user interface mechanisms were developed to provide easy access for marine ecologists, who wanted to explore the dataset. The book is a useful resource for system builders, as it gives an overview of the many new methods that were created to build the Fish4Knowledge system in a manner that also allows readers to see how all the components fit together.
Editors and Affiliations
Bibliographic Information
Book Title: Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data
Editors: Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-319-30208-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2016
Hardcover ISBN: 978-3-319-30206-5Published: 04 April 2016
Softcover ISBN: 978-3-319-80750-8Published: 25 April 2018
eBook ISBN: 978-3-319-30208-9Published: 24 March 2016
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XVII, 319
Number of Illustrations: 122 b/w illustrations, 13 illustrations in colour
Topics: Computational Intelligence, Image Processing and Computer Vision, Fish & Wildlife Biology & Management, Artificial Intelligence