000			01933cam a22003618i 4500
999			_c229 _d229
001			21025711
005			20251027105619.0
008			190619s2020 nyu b 001 0 eng
010			_a 2019025856
020			_a9780367254308 _q(hardback)
020			_z9780429289460 _q(ebook)
040			_aDLC _beng _erda _cNMSCST
042			_apcc
050	0	0	_aS675 _b.Z49 2020
082	0	0	_a631.5233 _bZ637 2020
100	1		_aZhongzhi, Han, _d1981- _eauthor.
245	1	0	_aComputer vision-based agriculture engineering / _cHan Zhongzhi.
263			_a1910
264		1	_aNew York, NY : _bCRC Press, Taylor & Francis Group, _cc2020.
300			_axvii, 329 pages : _billustrations
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_a"Computer Vision-Based Agriculture Engineering is a summary of the author's work over the past 10 years. Professor Han has presented his most recent research results in the book of all 25 chapters. This unique work provides student, engineers and technologists working in research, development, and operations in the agricultural engineering with critical, comprehensive and readily accessible information. The book applies development of artificial intelligence theory and methods including depth learning and transfer learning to the field of agricultural engineering testing"-- _cProvided by publisher.
650		0	_aAgricultural engineering _xTechnological innovations.
650		0	_aAgriculture _xRemote sensing.
650		0	_aQuality control _xOptical methods.
776	0	8	_iOnline version: _aZhongzhi, Han, _tComputer vision-based agriculture engineering _dBoca Raton : Taylor & Francis, 2019. _z9780429289460 _w(DLC) 2019025857
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cCIR