Coverart for item
The Resource Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data, edited by Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin, (electronic resource)

Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data, edited by Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin, (electronic resource)

Label
Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data
Title
Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data
Statement of responsibility
edited by Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin
Contributor
Subject
Language
eng
Summary
  • 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
  • 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
  • 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
Member of
Is part of
Dewey number
006.3
LC call number
Q342
http://library.link/vocab/relatedWorkOrContributorName
  • Fisher, Robert B
  • Chen-Burger, Yun-Heh
  • Giordano, Daniela
  • Hardman, Lynda
  • Lin, Fang-Pang
  • SpringerLink (Online service)
Series statement
Intelligent Systems Reference Library,
Series volume
104
http://library.link/vocab/subjectName
  • Engineering
  • Artificial intelligence
  • Wildlife
  • Fish
  • Computational intelligence
  • Engineering
  • Computational Intelligence
  • Artificial Intelligence (incl. Robotics)
  • Fish & Wildlife Biology & Management
Label
Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data, edited by Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin, (electronic resource)
Instantiates
Publication
Contents
  • 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
  • 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
  • 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
Control code
OCM1bookssj0001654045
Dimensions
unknown
Edition
1st ed. 2016.
Isbn
9783319302089
Other control number
10.1007/978-3-319-30208-9
Specific material designation
remote
System control number
(WaSeSS)bookssj0001654045
Label
Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data, edited by Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin, (electronic resource)
Publication
Contents
  • 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
  • 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
  • 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
Control code
OCM1bookssj0001654045
Dimensions
unknown
Edition
1st ed. 2016.
Isbn
9783319302089
Other control number
10.1007/978-3-319-30208-9
Specific material designation
remote
System control number
(WaSeSS)bookssj0001654045

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      400 West 14th Street, Rolla, MO, 65409, US
      37.955220 -91.772210
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