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008			160324s2016 gw | s |||| 0|eng d
020			_a9783319302089
040			_aES-MaUEC
050		4	_aQL125 _b.F574 2016
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245	1	0	_aFish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data _cedited by Robert B Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XVII, 319 páginas) _b135 ilustraciones, 13 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aIntelligent Systems Reference Library _x1868-4394 _v104
505	0		_aOverview 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.
520	3		_aThis 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.
650		7	_aInteligencia artificial _0comprobar BNE19900997218 _2embne _9413115
650	0	7	_aFlora costera _9189917 _2embne
700	1		_aFisher, Robert B. _eeditor literario _998811 _0Local
700	1		_aChen-Burger, Yun-Heh _eeditor literario _0Local _998812
700	1		_aGiordano, Daniela. _eeditor literario _943024
700	1		_aHardman, Lynda _eeditor literario _0Local _998813
700	1		_aLin, Fang-Pang. _eeditor literario _998814 _0Local
710	2		_aSpringerLink (Online service) _0Local _9106996
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-30208-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319302089
907			_a.b12949590 _b10-10-17 _c21-11-16
942			_2lcc _cLE
945			_aQL125 .F574 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11592813 _z06-04-17
988			_aEBOOK, asignarmaterias , EBSPRINGER
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0