000			04138cam a2200529Ki 4500
001			9781003162810
003			FlBoTFG
005			20240213122825.0
006			m o d
007			cr cnu|||unuuu
008			211007s2022 xx eo 000 0 eng d
040			_aOCoLC-P _beng _erda _epn _cOCoLC-P
020			_a9781003162810 _q(electronic bk.)
020			_a1003162819 _q(electronic bk.)
020			_z9780367755287
020			_z9780367744700
020			_a9781000540925 _q(electronic bk. : PDF)
020			_a1000540928 _q(electronic bk. : PDF)
020			_a9781000540963 _q(electronic bk. : EPUB)
020			_a1000540960 _q(electronic bk. : EPUB)
035			_a(OCoLC)1273727604
035			_a(OCoLC-P)1273727604
050		4	_aTA1634
072		7	_aCOM _x012000 _2bisacsh
072		7	_aCOM _x012040 _2bisacsh
072		7	_aCOM _x016000 _2bisacsh
072		7	_aUYQ _2bicssc
082	0	4	_a006.3/7 _223/eng/20211028
245	0	0	_aLow-power computer vision : _bimprove the efficiency of artificial intelligence / _cedited by George K. Thiruvathukal, Yung-Hsiang Lu, Jaeyoun Kim, Yiran Chen, Bo Chen.
250			_aFirst edition.
264		1	_a[Place of publication not identified] : _bChapman and Hall/CRC, _c2022.
300			_a1 online resource (344 pages).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
505	0		_aSection I IntroductionBook IntroductionYung-Hsiang Lu, George K. Thiruvathukal, Jaeyoun Kim, Yiran Chen, and Bo ChenHistory of Low-Power Computer Vision ChallengeYung-Hsiang Lu and Xiao Hu, Yiran Chen, Joe Spisak, Gaurav Aggarwal, Mike Zheng Shou, and George K. ThiruvathukalSurvey on Energy-Efficient Deep Neural Networks for Computer VisionAbhinav Goel, Caleb Tung, Xiao Hu, Haobo Wang, and Yung-Hsiang Lu and George K. ThiruvathukalSection II Competition WinnersHardware design and software practices for efficient neural network inferenceYu Wang, Xuefei Ning, Shulin Zeng, Yi Kai, Kaiyuan Guo, and Hanbo Sun, Changcheng Tang, Tianyi Lu, Shuang Liang, and Tianchen ZhaoProgressive Automatic Design of Search Space for One-Shot Neural Architecture SearchXin Xia, Xuefeng Xiao, and Xing WangFast Adjustable Threshold For Uniform Neural Network QuantizationAlexander Goncharenko, Andrey Denisov, and Sergey AlyamkinPower-efficient Neural Network Scheduling on Heterogeneous SoCsYing Wang, Xuyi Cai, and Xiandong ZhaoEfficient Neural Network ArchitecturesHan Cai and Song HanDesign Methodology for Low Power Image Recognition SystemsSoonhoi Ha, EunJin Jeong, Duseok Kang, Jangryul Kim, and Donghyun KangGuided Design for Efficient On-device Object Detection ModelTao Sheng and Yang LiuSection III Invited ArticlesQuantizing Neural NetworksMarios Fournarakis, Markus Nagel, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, and Tijmen BlankevoortA practical guide to designing efficient mobile architecturesMark Sandler and Andrew HowardA Survey of Quantization Methods for Efficient Neural Network InferenceAmir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael Mahoney, and Kurt KeutzerBibliographyIndex
520			_aEnergy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.
588			_aOCLC-licensed vendor bibliographic record.
650		7	_aCOMPUTERS / Computer Graphics / General _2bisacsh
650		7	_aCOMPUTERS / Computer Graphics / Game Programming & Design _2bisacsh
650		7	_aCOMPUTERS / Computer Vision & Pattern Recognition _2bisacsh
650		0	_aComputer vision.
650		0	_aLow voltage systems.
700	1		_aThiruvathukal, George K. _q(George Kuriakose), _eeditor.
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781003162810
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999			_c4935 _d4935