000			02075cam a22003018i 4500
001			10802
003			IN-BhIIT
005			20240912135742.0
008			200524s2020 flu b 001 0 eng
020			_a9780367518981
040			_aIN-BhIIT
041			_aeng
082	0	0	_a621.3678 _bCRE/D
100	1		_aCresson, Remi, _eAuthor. _923534
245	1	0	_aDeep learning for remote sensing images with open source software / _cby Remi Cresson.
260			_aBoca Raton : _bCRC Press, _c2020.
300			_ax,151 p. : _bill. ; _c24 cm.
504			_aIncludes bibliographical references and index.
505	0		_aDeep learning backgrounds -- Software -- Data used : the Tokyo dataset -- A simple convolutional neural network -- Fully convolutional neural network -- Classifiers on deep features -- Dealing with multiple sources -- Semantic segmentation of optical imagery -- Data used : the Amsterdam dataset -- Mapping buildings -- Gap filling of optical images : principle -- The Marmande dataset -- Pre-processing -- Model training -- Inference.
520			_a"In today's world, deep learning source codes and a plethora of open access geospatial images are available, but readers are missing the educational tools. This is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches are generic and adapted to suit many applications for various remote sensing images processing in landcover mapping, forestry, urban, in disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps readers link together the theory and practical use of existing tools and data to create their own remote sensing data processing"--
650		0	_aRemote sensing _xData processing. _923535
650		0	_aRemote-sensing images. _922
650		0	_aImage processing _xDigital techniques. _92008
650		0	_aMachine learning. _924707
650		0	_aNeural networks (Computer science). _96883
650		0	_aOpen source software. _95250
942			_cTRB _01
999			_c13668 _d13668