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008			170817s2018 gw | s |||| 0|eng d
020			_a9783319613161
024	7		_a10.1007/978-3-319-61316-1 _2doi
040			_bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1637 _b.B565 2018 EB
245	1	0	_aBiologically Rationalized Computing Techniques For Image Processing Applications _cedited by Jude Hemanth, Valentina Emilia Balas.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (VI, 337 páginas 210 ilustraciones, 147 ilustraciones a color.)
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aLecture Notes in Computational Vision and Biomechanics, _x2212-9391 _v25
490	0		_aEngineering (Springer-11647)
505	0		_aArtifical Bee Colony Algorithm for Classification of Semi-Urban LU/LC Features Using High Resolution Satellite Data.- Saliency Based Image Compression Using Walsh-Hadamard Transform (WHT).- Object trajectory prediction with scarce environment information.- A Two-fold Subspace Learning Based Feature Fusion Strategy for Classification of EMG and EMG spectrogram Images.- Automatic Detection of Brain Strokes in CT Images using Soft Computing Techniques.- A survey on Intelligence based biometric techniques for authentication applications.- Spatial and Spectral Quality Assessment of Fused Hyperspectral and Multispectral Data.- Deep Learning Techniques for Breast Cancer Detection using Medical Images Analysis.- A Tour towards the development of various Techniques for Paralysis Detection using Image Processing.- Chlorella - Algae Image Analysis using Artificial Neural Network and Deep Learning.- Review on Image Enhancement Techniques using Biologically Inspired Artificial Bee Colony Algorithms and its variants.- Certain Applications and Case Studies of Evolutionary Computing Techniques for Image Processing -- Histopathological Image Analysis for the Grade Identification of Tumor -- Super Resolution via Particle Swarm Optimization Variants. .
520	3		_aThis book introduces readers to innovative bio-inspired computing techniques for image processing applications. It demonstrates how a significant drawback of image processing - not providing the simultaneous benefits of high accuracy and less complexity - can be overcome, proposing bio-inspired methodologies to help do so.  Besides computing techniques, the book also sheds light on the various application areas related to image processing, and weighs the pros and cons of specific methodologies. Even though several such methodologies are available, most of them do not provide the simultaneous benefits of high accuracy and less complexity, which explains their low usage in connection with practical imaging applications, such as the medical scenario. Lastly, the book illustrates the methodologies in detail, making it suitable for newcomers to the field and advanced researchers alike.
988			_aEBSPRINGER_2018
650		7	_2embne _9150920 _aFotónica
700	1		_aHemanth, Jude. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _1http://viaf.org/viaf/40147663093160551999/
700	1		_aBalas, Valentina Emilia _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/no2009108627 _1http://viaf.org/viaf/206147663095060552229/ _996925
776	0	8	_iEdición impresa: _z9783319613154
776	0	8	_iEdición impresa: _z9783319613178
776	0	8	_iEdición impresa: _z9783319870502
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-61316-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE