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Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data Softcover reprint of the original 1st ed. 2016 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 319 pages, height x width: 235x155 mm, weight: 5153 g, 13 Illustrations, color; 122 Illustrations, black and white; XVII, 319 p. 135 illus., 13 illus. in color., 1 Paperback / softback
  • Sērija : Intelligent Systems Reference Library 104
  • Izdošanas datums: 25-Apr-2018
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319807501
  • ISBN-13: 9783319807508
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  • Formāts: Paperback / softback, 319 pages, height x width: 235x155 mm, weight: 5153 g, 13 Illustrations, color; 122 Illustrations, black and white; XVII, 319 p. 135 illus., 13 illus. in color., 1 Paperback / softback
  • Sērija : Intelligent Systems Reference Library 104
  • Izdošanas datums: 25-Apr-2018
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319807501
  • ISBN-13: 9783319807508
Citas grāmatas par šo tēmu:
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.
Overview
of the Fish4Knowledge Project.- User Information
Needs.- Supercomputing Resources.- Marine Video Data Capture and
Storage.- Logical Data Resource Storage.- Software Architecture with
Flexibility
for the Data-Intensive Fish4Knowledge Project.- Fish4Knowledge Database
Structure,
Creating and Sharing Scientific Data).- Intelligent Workflow Management
for Fish4Knowledge using the SWELL System.- Fish Detection.- Fish
Tracking.- Hierarchical Classification System with Reject Option for Live
Fish Recognition.- Fish Behavior Analysis.- Understanding
Uncertainty Issues in the Exploration of Fish Counts.- Data Groundtruthing
and Crowdsourcing.- Counting on Uncertainty: Obtaining Fish Counts from
Machine Learning
Decisions.- Experiments with the Full Fish4Knowledge Dataset.- The
Fish4Knowledge Virtual World Gallery.- Conclusions.