000			03741nam a22003855i 4500
001			298417
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008			150903s2008 gw | o |||| 0|eng d
020			_a9783540793533 _99783540793533
024	7		_a10.1007/9783540793533 _2doi
035			_avtls000351849
039		9	_a201509030450 _bVLOAD _c201405060256 _dVLOAD _y201402171146 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTA329-348
100	1		_aGraña, Manuel. _eeditor. _9323145
245	1	0	_aComputational Intelligence for Remote Sensing / _cedited by Manuel Graña, Richard J. Duro.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2008.
300			_brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aStudies in Computational Intelligence, _x1860-949X ; _v133
500			_aSpringer eBooks
505	0		_aOptical Configurations for Imaging Spectrometers -- Remote Sensing Data Compression -- A Multiobjective Evolutionary Algorithm for Hyperspectral Image Watermarking -- Architecture and Services for Computational Intelligence in Remote Sensing -- On Content-Based Image Retrieval Systems for Hyperspectral Remote Sensing Images -- An Analytical Approach to the Optimal Deployment of Wireless Sensor Networks -- Parallel Spatial-Spectral Processing of Hyperspectral Images -- Parallel Classification of Hyperspectral Images Using Neural Networks -- Positioning Weather Systems from Remote Sensing Data Using Genetic Algorithms -- A Computation Reduced Technique to Primitive Feature Extraction for Image Information Mining Via the Use of Wavelets -- Neural Networks for Land Cover Applications -- Information Extraction for Forest Fires Management -- Automatic Preprocessing and Classification System for High Resolution Ultra and Hyperspectral Images -- Using Gaussian Synapse ANNs for Hyperspectral Image Segmentation and Endmember Extraction -- Unsupervised Change Detection from Multichannel SAR Data by Markov Random Fields.
520			_aThis book is a composition of different points of view regarding the application of Computational Intelligence techniques and methods to Remote Sensing data and applications. It is the general consensus that classification, its related data processing, and global optimization methods are core topics of Computational Intelligence. Much of the content of the book is devoted to image segmentation and recognition, using diverse tools from different areas of the Computational Intelligence field, ranging from Artificial Neural Networks to Markov Random Field modeling. The book covers a broad range of topics, starting from the hardware design of hyperspectral sensors, and data handling problems, namely data compression and watermarking issues, as well as autonomous web services. The main contents of the book are devoted to image analysis and efficient (parallel) implementations of these analysis techniques. The classes of images dealt with throughout the book are mostly multispectral-hyperspectral images, though there are some instances of processing Synthetic Aperture Radar images.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aDuro, Richard J. _eeditor. _9160868
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540793526
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-79353-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c298417 _d298417