"Ch. 3. Learning Control Strategies for Object Recognition"

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Book	Author(s)	Year	Publisher
Deep Learning in Object Detection and Recognition	Xiaoyue Jiang; Abdenour Hadid; Yanwei Pang; Eric Granger; Xiaoyi Feng	1st ed. 2019	Springer Nature Singapore
Object Recognition	Tam Phuong Cao	2011-04-01	IntechOpen
Object recognition by 3-dimensional curve matching.	C. Marc Bastuscheck	1986	Courant Institute of Mathematical Sciences, New York University
Visual Object Recognition	Kristen Grauman; Bastian Leibe		Springer International Publishing
Visual object recognition	Kristen Lorraine Grauman	2011	Morgan & Claypool
Natural object recognition	Thomas M. Strat	1992	Springer-Verlag
Natural Object Recognition	Thomas M. Strat	1992	Springer New York
Automatic model builder for object recognition.	C. Marc Bastuscheck	1987	Courant Institute of Mathematical Sciences, New York University
Teaching word recognition: effective strategies for students with learning difficulties	Rollanda E. O'Connor	2014	Guilford Publications
Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python	Himanshu Singh	1st ed.	Apress
Object and face recognition	Bruce/Hump	1994	Lawrence Erlbaum Associates
Fast learning and invariant object recognition: the sixth-generation breakthrough	Branko Souček	1992	Wiley
Integrating Graphics and Vision for Object Recognition	Mark R. Stevens; J. Ross Beveridge	2001	Springer US
Indoor Scene Recognition by 3-D Object Search: For Robot Programming by Demonstration	Pascal Meißner	1st ed. 2020	Springer International Publishing
Machine Learning for Speaker Recognition	Man-Wai Mak; Jen-Tzung Chien	2020-11	Cambridge University Press
Deep Learning for Computer Vision: Image Classification, Object Detection, and Face Recognition in Python	Jason Brownlee	2019	Independently Published
Toward Category-Level Object Recognition	Jean Ponce; Martial Hebert; Cordelia Schmid; Andrew Zisserman	2006	Springer Berlin Heidelberg
Object Recognition, Attention, and Action	Naoyuki Osaka; Ingo Rentschler; Irving Biederman	2007	Springer Japan
Borb: Birmingham Object Recognition Battery	Jane M. Riddoch; Glyn W. Humphreys	1993	Routledge
Object recognition through invariant indexing /	Rothwell, Charles A.	1995.	Oxford University Press,
Boook	Author(s)	Year	Publisher

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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Ch. 3. Learning Control Strategies for Object Recognition	Bruce A. Draper	Symbolic visual learning /	Ikeuchi, Katsushi.; Veloso, Manuela M.	1997.	Oxford University Press,
Ch. 3. Object recognition		Cognitive psychology: a student's handbook /	Eysenck, Michael W.; Keane, Mark T.,	[1995], ©1995.	Erlbaum,
Ch. 9. Memorization Learning for Object Recognition	Randal C. Nelson	Early visual learning /	Nayar, Shree K.; Poggio, Tomaso.	1996.	Oxford University Press,
Attentional strategies for object recognition	Luiz Pessoa; Sergio Exel	Foundations and Tools for Neural Modeling: International Work-Conference on Artificial and Natural Neural Networks, IWANN' 99, Alicante, Spain, June 2-4, 1999, Proceedings, Volume I	José Mira; Juan V. Sánchez-Andrés	1999	Springer Berlin Heidelberg
Learning Features for Object Recognition	Yingqiang Lin; Bir Bhanu	Genetic and Evolutionary Computation — GECCO 2003: Genetic and Evolutionary Computation Conference Chicago, IL, USA, July 12–16, 2003 Proceedings, Part II	Erick Cantú-Paz; James A. Foster; Kalyanmoy Deb; Lawrence David Davis; Rajkumar Roy; Una-May O'Reilly; Hans-Georg Beyer; Russel Standish; Graham Kendall; Stewart Wilson; Joachim Wegener; Dipankar Dasgupta; Mitchell A. Potter; Alan C. Schultz	2003	Springer Berlin Heidelberg
Deep Learning for Object Recognition		Deep Learning for Computer Vision: Image Classification, Object Detection, and Face Recognition in Python	Jason Brownlee	2019	Independently Published
Unsupervised Learning of Biologically Plausible Object Recognition Strategies	Bruce A. Draper; Kyungim Baek	Biologically Motivated Computer Vision: First IEEE International Workshop BMCV 2000, Seoul, Korea, May 15-17, 2000 Proceedings	Seong-Whang Lee; Heinrich H. Bülthoff; Tomaso Poggio	2000	Springer Berlin Heidelberg
Coevolutionary Feature Learning for Object Recognition	Krzysztof Krawiec; Bir Bhanu	Machine Learning and Data Mining in Pattern Recognition: Third International Conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003, proceedings	Petra Perner; Azriel Rosenfeld	2003	Springer Berlin Heidelberg
Learning appearance models for object recognition	Arthur R. Pope; David G. Lowe	Object Representation in Computer Vision II: ECCV ' 96 International Workshop, Cambridge, UK, April 13 - 14, 1996. Proceedings	Jean Ponce; Andrew Zisserman; Martial Hebert	1996	Springer Berlin Heidelberg
Active Metric Learning for Object Recognition	Sandra Ebert; Mario Fritz; Bernt Schiele	Pattern Recognition: Joint 34th DAGM and 36th OAGM Symposium, Graz, Austria, August 28-31, 2012, Proceedings	Axel Pinz; Thomas Pock; Horst Bischof; Franz Leberl	2012	Springer Berlin Heidelberg
Ch. 4. Learning Probabilistic Appearance Models for Object Recognition	Arthur R. Pope and David G. Lowe	Early visual learning /	Nayar, Shree K.; Poggio, Tomaso.	1996.	Oxford University Press,
Object Reading: Text Recognition for Object Recognition	Sezer Karaoglu; Jan C. van Gemert; Theo Gevers	Computer Vision -- ECCV 2012. Workshops and Demonstrations: Florence, Italy, October 7-13, 2012, Proceedings, Part III	Andrea Fusiello; Vittorio Murino; Rita Cucchiara	2012	Springer Berlin Heidelberg
Ch. 4. PADO: A New Learning Architecture for Object Recognition	Astro Teller and Manuela Veloso	Symbolic visual learning /	Ikeuchi, Katsushi.; Veloso, Manuela M.	1997.	Oxford University Press,
Ch 1. Strategies for learning		Study skills for nurses	Morgan Merrington	2009	Juta
Ensemble Learning for Object Recognition and Tracking	Mehrtash Harandi; Javid Taheri; Brian C. Lovell	Pattern Recognition, Machine Intelligence and Biometrics	Patrick S. P. Wang	2011	Springer Berlin Heidelberg
Unsupervised Selective Transfer Learning for Object Recognition	Wei-Shi Zheng; Shaogang Gong; Tao Xiang	Computer Vision - ACCV 2010: 10th Asian Conference on Computer Vision, Queenstown, New Zealand, November 8-12, 2010, Revised Selected Papers, Part II	Ron Kimmel; Reinhard Klette; Akihiro Sugimoto	2011	Springer Berlin Heidelberg
Invariant visual object recognition learning		Memory, Attention, and Decision-Making: A Unifying Computational Neuroscience Approach	Edmund T. Rolls	2007	Oxford University Press
Invariant visual object recognition learning		Cerebral Cortex: Principles of Operation	Edmund T. Rolls	2016	Oxford University Press
3-D Object Creation for Recognition	M. Bennamoun; G. J. Mamic	Object Recognition: Fundamentals and Case Studies	M. Bennamoun; G.J. Mamic	2002	Springer London
Ch. 2. MULTI-HASH: Learning Object Attributes and Hash Tables for Fast 3-D Object Recognition	Lynne Grewe and Avi Kak	Symbolic visual learning /	Ikeuchi, Katsushi.; Veloso, Manuela M.	1997.	Oxford University Press,
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