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020			_a9781138747951
040			_aCIBESPAM MFL
041			_aeng
082			_a006.3 _bV461
100			_aVenkatesan, Ragav
245			_aConvolutional Neural Networks in Visual Computing. _bA Concise Guide.
260			_aLondon _bTaylor & Francis, CRC Press _c2017
300			_axviii, 168 pages; _bFigures;
505			_a-Dedication -Acknowledgements -About the Author -Preface -Chapter 1: Introduction to visual computing -Chapter 2: Learning as a regression problem -Chapter 3: Artificial neural networks -Chapter 4: Convolutional neural networks -Chapter 5: Modern and novel usages of CNNs -Appendix -Postscript
520			_aThis book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.
650			_aComputer vision
650			_aNeural networks
650			_aComputer sicence
700			_aLi, Baoxin
912			_c2024-01-04 _dPául Villacreses
913			_aTIC _bCC _dSCSAS
942			_2ddc _cBK
999			_c13029 _d13029