14.5.1 Learning, General Surveys, Overviews

Chapter Contents (Back)
Survey, Learning. Learning. BibRef 7700

Schwartz, S.R., Wah, B.W.,
Machine Learning of Computer Vision Algorithms,
HPRIP-CV94(319-359). BibRef 9400

Fu, K.S., ed.,
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Bhanu, B., Poggio, T.,
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Bhanu, B., Peng, J., Huang, T., Draper, B.,
Introduction to the Special Issue on Learning in Computer Vision and Pattern Recognition,
SMC-B(35), No. 3, June 2005, pp. 391-396.
WWW Version. 0508 BibRef

Vapnik, V.,
The Nature of Statistical Learning Theory,
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Vapnik, V.,
Statistical Learning Theory,
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Poggio, T.[Tomaso], Shelton, C.R.[Christian R.],
Machine Learning, Machine Vision, and the Brain,
AIMag(20), No. 3, Fall 1999, pp. 37-55. Regularization. Support Vector Machines. Survey, Learning. Survey of learning focused on a vision domain. Regularization, Support Vector Machines. Applied to face and pedestrian recognition. BibRef 9900

Petrou, M.[Maria],
Learning in Pattern Recognition: Some Thoughts,
PRL(22), No. 1, January 2001, pp. 3-13.
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Petrou, M.[Maria],
Learning in Computer Vision: Some Thoughts,
CIARP07(1-12).
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Freeman, W.[William], Perona, P.[Pietro], Schölkopf, B.[Bernhard],
Guest Editorial Machine Learning for Vision,
IJCV(77), No. 1-3, May 2008, pp. 1.
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Raducanu, B., Vitria, J.,
Learning to learn: From smart machines to intelligent machines,
PRL(29), No. 8, 1 June 2008, pp. 1024-1032.
WWW Version. 0804Intelligent systems; Cognitive development; Context; Social robotics; Face recognition BibRef


Bala, J.W., Michalski, R.S., and Pachowicz, P.W.,
Progress on Vision through Learning at George Mason University,
ARPA94(I:191-207). BibRef 9400

Michalski, R.S., Rosenfeld, A., Aloimonos, Y., Duric, Z., Maloof, M.A., Zhang, Q.,
Progress on Vision Through Learning,
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Nagy, G.[George],
Persistent Issues in Learning and Estimation,
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Bhanu, B.[Bir], Bowyer, K.W.[Kevin W.], Hall, L.O.[Lawrence O.], and Langley, P.[Pat],
Report of the AAAI Fall Symposium on Machine Learning and Computer Vision: What, Why and How?,
ARPA94(I:727-731). BibRef 9400

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Evaluation and Analysis of Learning Techniques .


Last update:Jun 25, 2008 at 13:37:57