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008			161216s2017 gw ob 001 0 eng d
020			_a3662537451 _q(electronic bk.)
020			_a9783662537459 _q(electronic bk.)
020			_z3662537435
020			_z9783662537435
035			_a(OCoLC)966205922 _z(OCoLC)965904347 _z(OCoLC)967861662 _z(OCoLC)970782460 _z(OCoLC)971047276 _z(OCoLC)974650301 _z(OCoLC)981111328 _z(OCoLC)1005800745 _z(OCoLC)1012074449
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050		4	_aQK46.5.E4 _bR463 2017 EB
100	1		_aRemagnino, Paolo, _9677293 _d1963- _eautor
245	1	0	_aComputational botany : _bmethods for automated species identification. _cPaolo Remagnino
264		1	_a[Berlin] _bSpringer _c2017
300			_a1 recurso en línea
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
500			_aSpringerLink
504			_aIncluye referencias bibliográficas e índice
505	0		_aFrom the Content -- Introduction -- Morphometrics: a Brief Review -- Feature Extraction -- Machine Learning for Plant Leaf Analysis.
520	3		_aThis book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist's perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert's fixation process. The book not only represents an authoritative guide to advanced computational tools for plant identification, but provides experts in botany, computer science and pattern recognition with new ideas and challenges. As such it is expected to foster both closer collaborations and further technological developments in the emerging field of automatic plant identification.
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017B
650		7	_aInteligencia artificial _2embne _0(OCoLC)fst00871995 _0 _9413115
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-662-53745-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2018 _dz _e- _zSI