000			03523nam a22004453i 4500
001			EBC6963478
003			MiAaPQ
005			20250821101107.0
006			m o d |
007			cr cnu||||||||
008			250807s2022 xx o ||||0 eng d
020			_a9783030909871 _q(electronic bk.)
020			_z9783030909864
035			_a(MiAaPQ)EBC6963478
035			_a(Au-PeEL)EBL6963478
035			_a(OCoLC)1313386673
040			_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ
100	1		_aBetti, Alessandro.
245	1	0	_aDeep Learning to See : _bTowards New Foundations of Computer Vision.
250			_a1st ed.
264		1	_aCham : _bSpringer International Publishing AG, _c2022.
264		4	_c�2022.
300			_a1 online resource (116 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aSpringerBriefs in Computer Science Series
505	0		_aIntro -- Preface -- Acknowledgements -- Contents -- 1 Motion Is the Protagonist of Vision -- 1.1 Introduction -- 1.2 The Big Picture -- 1.3 Supervised Learning Is an Artificial Learning Protocol -- 1.4 Cutting the Umbilical Cord with Pattern Recognition -- 1.5 Dealing with Video Instead of Images -- 1.6 Ten Questions for a Theory of Vision -- 2 Focus of Attention -- 2.1 Introduction -- 2.2 How Can Humans Perform Pixel Semantic Labeling? -- 2.3 Insights from Evolution of the Animal Visual System -- 2.4 Why Focus of Attention? -- 2.5 What Drives Eye Movements? -- 2.6 The Virtuous Loop of Focus of Attention -- 3 Principles of Motion Invariance -- 3.1 Introduction -- 3.2 Computational Models in Spatiotemporal Environments -- 3.3 Object Identity and Affordance -- 3.4 From Material Points to Pixels -- 3.5 The Principle of Material Point Invariance -- 3.6 The Principle of Coupled Motion Invariance -- 3.7 Coupling of Vision Fields -- 4 Foveated Neural Networks -- 4.1 Introduction -- 4.2 Why Receptive Fields and Hierarchical Architectures? -- 4.3 Why Two Different Mainstreams? -- 4.4 Foveated Nets and Variable Resolution -- 5 Information-Based Laws of Feature Learning -- 5.1 The Simplest Case of Feature Conjugation -- 5.2 Neural Network Representation of the Velocity Field -- 5.3 A Dynamic Model for Conjugate Features and Velocities -- 5.4 Online Learning -- 5.5 Online Learning: An Optimal Control Theory Prospective -- 5.6 Why is Baby Vision Blurred? -- 6 Non-visual Environmental Interactions -- 6.1 Object Recognition and Related Visual Skills -- 6.2 What Is the Interplay with Language? -- 6.3 The ``en Plein Air'' Perspective -- Appendix A Calculus of Variations -- A.1 Integral Functional and Euler Equations -- Appendix References -- -- Index.
588			_aDescription based on publisher supplied metadata and other sources.
590			_aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2025. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
650		0	_aComputer vision.
655		4	_aElectronic books.
700	1		_aGori, Marco.
700	1		_aMelacci, Stefano.
776	0	8	_iPrint version: _aBetti, Alessandro _tDeep Learning to See _dCham : Springer International Publishing AG,c2022 _z9783030909864
797	2		_aProQuest (Firm)
830		0	_aSpringerBriefs in Computer Science Series
856	4	0	_uhttps://ebookcentral-proquest-com.mlisicats.remotexs.co/lib/ppks/detail.action?docID=6963478&query=9783030909871 _zClick to View
942			_2lcc _cEB
999			_c1954 _d1954