000			02177nam a22003495c 4500
001			86218
003			ES-MaUEC
005			20230202105050.0
008			160908s2016 gw | s |||| 0|eng d
020			_a9783319409917
040			_aES-MaUEC
050		4	_aTA1634 _b.W895 2016 EB
082	0	4	_a006.6
082	0	4	_a006.37
100	1		_aWu, Ziyan _999776 _0Local
245	1	0	_aHuman Re-Identification _cby Ziyan Wu
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XV, 104 p.) _b40 ilustraciones
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	1		_aMultimedia Systems and Applications
520			_aThis book covers aspects of human re-identification problems related to computer vision and machine learning. Working from a practical perspective, it introduces novel algorithms and designs for human re-identification that bridge the gap between research and reality. The primary focus is on building a robust, reliable, distributed and scalable smart surveillance system that can be deployed in real-world scenarios. This book also includes detailed discussions on pedestrian candidates detection, discriminative feature extraction and selection, dimension reduction, distance/metric learning, and decision/ranking enhancement. This book is intended for professionals and researchers working in computer vision and machine learning. Advanced-level students of computer science will also find the content valuable.
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGER
650		7	_aVisión por ordenador _0comprobar BNE20020695437 _2embne _9159793
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-40991-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319409917
907			_a.b12954962 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b03-05-17 _cm _dz _ef _feng _ggw _h0
945			_aTA1634 .W895 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11597227 _z06-04-17
999			_c86218 _d86218 _x1