000			03019cam a2200313 i 4500
001			22775615
003			CUTN
005			20230816143657.0
008			220902s2021 stka b 001 0 eng
010			_a 2020479788
020			_a9781849951289 _q(hbk.)
040			_aDLC _beng _erda _cDLC
042			_apcc
050	0	0	_aTK7882.P3 _bO35 2011
082			_a006.4 _bHIZ
245	0	0	_aObject and pattern recognition in remote sensing : _bmodelling and monitoring environmental and anthropogenic objects and change processes / _cedited by S. Hinz, A.C. Braun, M. Weinmann.
260			_aScotland : _bWhittles Publishing, _c2021.
300			_axiii, 350 pages : _billustrations (some color) ; _c24 cm
504			_aIncludes bibliographical references and index.
520			_aAbout the Book: Object and Pattern Recognition in Remote Sensing: Modelling and Monitoring Environmental and Anthropogenic Objects and Change Processes Fully automated interpretation and understanding of remotely sensed data by a computer has been a challenge for many decades, and many approaches have been developed over the years. Significant advances in knowledge-based image understanding, machine learning and artificial intelligence has led to this topic being the focus of much research in recent years. This book highlights the different theoretical and application-oriented aspects and potential solutions to the topic of automated remote sensing data analysis. Thereby, both classical knowledge-based as well as modern machine learning-oriented concepts are described. A field such as this is specialized and dynamic and also interdisciplinary and multilayered. Written by an international team of experts, the book has therefore been split into parts dealing with the concepts and applications, and the focus is on elucidating the complementarity of different lines of research rather than providing the complete set of scientific approaches. Part A of this book gives insight into the basic theories and concepts of feature extraction, image understanding and the respective assessment strategies as well as into geometric, radiometric and sensor-related fundamentals of remote sensing technology. Part B focuses on various scientific and practical applications of remote sensing data analysis. These range from the automatic detailed reconstruction of complex 3D environments to visual tracking of objects in image sequences as well as monitoring natural and anthropogenic long-term processes on a regional scale. Part C sketches recent trends in automatic analysis of remote sensing data.
650		0	_aPattern recognition systems.
650		0	_aRemote sensing.
700	1		_aHinz, Stefan _c(Professor of remote sensing and image processing), _eeditor.
700	1		_aBraun, Andreas Christian, _d1982- _eeditor.
700	1		_aWeinmann, Martin _c(Researcher), _eeditor.
906			_a7 _bcbc _corigres _d3 _encip _f20 _gy-gencatlg
942			_2ddc _cBOOKS
999			_c39646 _d39646