14.5 Learning in Computer Vision

Domke, J.[Justin], Karapurkar, A.[Alap], Aloimonos, Y.[Yiannis],
Who killed the directed model?,
CVPR08(1-8).
IEEE DOI Link 0806
MRF (an undirected model) has become popular. Learning can be expensive. Directed models require ordering variables. Learning is relatively simple. Applied to inpainting. BibRef

Jian, B.[Bing], Vemuri, B.C.[Baba C.],
Metric Learning Using Iwasawa Decomposition,
ICCV07(1-6).
IEEE DOI Link 0710
BibRef

Nomiya, H.[Hiroki], Uehara, K.[Kuniaki],
Multistrategical Approach in Visual Learning,
ACCV07(I: 502-511).
Springer DOI Link 0711
BibRef

Zheng, Y.[Yu], Luo, S.W.[Si-Wei], Lv, Z.[Ziang],
Control Double Inverted Pendulum by Reinforcement Learning with Double CMAC Network,
ICPR06(IV: 639-642).
WWW Version. 0609
BibRef

Autio, I.[Ilkka], Lindgren, J.T.,
Online Learning of Discriminative Patterns from Unlimited Sequences of Candidates,
ICPR06(II: 437-440).
WWW Version. 0609
BibRef

Maree, R.[Raphael], Stevens, B.[Benjamin], Geurts, P.[Pierre], Guern, Y.[Yves], Mack, P.[Philippe],
A machine learning approach for material detection in hyperspectral images,
OTCBVS09(106-111).
IEEE DOI Link 0906
BibRef

Ernst, D.[Damien], Marée, R.[Raphaël], Wehenkel, L.[Louis],
Reinforcement Learning with Raw Image Pixels as Input State,
IWICPAS06(446-454).
Springer DOI Link 0608
BibRef

Laven, K., Leishman, S., Roweis, S.,
A statistical learning approach to document image analysis,
ICDAR05(I: 357-361).
IEEE DOI Link 0508
BibRef

Mulligan, J., Grudic, G.,
Topological Mapping from Image Sequences,
LCV05(III: 43-43).
IEEE DOI Link 0507
BibRef

Xiong, H.L.[Hui-Lin], Swamy, M.N.S., Ahmad, M.O.,
Learning with the Optimized Data-Dependent Kernel,
LCV04(95).
IEEE DOI Link 0406
BibRef

Li, Y.[Yi], Shapiro, L.G.[Linda G.], Bilmes, J.A.[Jeff A.],
A Generative/Discriminative Learning Algorithm for Image Classification,
ICCV05(II: 1605-1612).
IEEE DOI Link 0510
BibRef

Leitner, R.[Raimund],
Learning 3D Object Recognition from an Unlabelled and Unordered Training Set,
ISVC07(I: 644-651).
Springer DOI Link 0711
BibRef

Leitner, R.[Raimund], Bischof, H.[Horst],
Recognition of 3D Objects by Learning from Correspondences in a Sequence of Unlabeled Training Images,
DAGM05(369).
Springer DOI Link 0509
BibRef

Muñoz, X.[Xavier], Bosch, A.[Anna], Martí, J.[Joan], Espunya, J.[Joan],
A Learning Framework for Object Recognition on Image Understanding,
IbPRIA05(II:311).
Springer DOI Link 0509
BibRef

Bekel, H.[Holger], Bax, I.[Ingo], Heidemann, G.[Gunther], Ritter, H.[Helge],
Adaptive Computer Vision: Online Learning for Object Recognition,
DAGM04(447-454).
WWW Version. 0505
BibRef

Qin, A.K., Suganthan, P.N.,
A novel kernel prototype-based learning algorithm,
ICPR04(IV: 621-624).
IEEE DOI Link 0409
BibRef

Luo, T.[Tong], Kramer, K., Samson, S., Remsen, A.,
Active learning to recognize multiple types of plankton,
ICPR04(III: 478-481).
IEEE DOI Link 0409
BibRef

Ko, J.[Jaepil], Kim, E.[Eunju], Byun, H.R.[Hye-Ran],
Improved N-division output coding for multiclass learning problems,
ICPR04(III: 470-473).
IEEE DOI Link 0409
BibRef

Leang, P., Bhanu, B.,
Learning integrated perception-based speed control,
ICPR04(I: 813-816).
IEEE DOI Link 0409
BibRef

Taylor, G.W.,
A reinforcement learning framework for parameter control in computer vision applications,
CRV04(496-503).
IEEE Abstract. IEEE Top Reference. 0408
BibRef

Miasnikov, A.D., Rome, J.E., Haralick, R.M.,
A hierarchical projection pursuit clustering algorithm,
ICPR04(I: 268-271).
IEEE DOI Link 0409
BibRef

Shi, D., Ng, G.S., Gao, J., Yeung, D.S.,
Critical vector learning to construct RBF classifiers,
ICPR04(III: 359-362).
IEEE DOI Link 0409
BibRef

Eriksson, M.[Martin], Carlsson, S.[Stefan],
Qualitative Characterization and Use of Prior Information,
SCIA03(792-799).
WWW Version. 0310
Model the set of possible events by algebraic inequalities. Learning proceeds by selecting those inequalities that show a consistent sign when applied to the training data set. The manifold of possible events estimated in this way will in general represent the qualitative properties of the events. BibRef

Takamatsu, J.[Jun],
Improving State Based Analysis for Learning from Observation,
CREST03(227-241). 0309
BibRef

Kubota, S., Mizutani, H., Kurosawa, Y.,
A discriminative learning criterion for the overall optimization of error and reject,
ICPR02(IV: 98-102).
IEEE DOI Link 0211
BibRef

Mizutani, H.[Hiroyuki],
Discriminative Learning for Minimum Error and Minimum Reject Classification,
ICPR98(Vol I: 136-140).
IEEE DOI Link 9808
BibRef

Seok, J.[Jinwuk], Lee, J.W.[Jeun-Woo],
The analysis of a stochastic differential approach for langevine comepetitive learning algorithm,
ICPR02(II: 80-83).
IEEE DOI Link 0211
BibRef

Kang, F.[Feng], Naphade, M.R.[Milind R.],
A Generalized Multiple Instance Learning Algorithm for Iterative Distillation and Cross-Granular Propagation of Video Annotations,
ICIP07(II: 205-208).
IEEE DOI Link 0709
BibRef
Earlier:
A Generalized Multiple Instance Learning Algorithm with Multiple Selection Strategies for Cross Granular Learning,
ICIP06(3213-3216). 0610

IEEE DOI Link BibRef

Naphade, M.R., Frey, B.J., Chen, L., Huang, T.S.,
Learning Sparse Multiple Cause Models,
ICPR00(Vol II: 642-647).
IEEE DOI Link
HTML Version. 0009
BibRef

Hong, P., Huang, T.S.,
Learning to Extract Temporal Signal Patterns from Temporal Signal Sequence,
ICPR00(Vol II: 648-651).
IEEE DOI Link
HTML Version. 0009
BibRef

Sato, A.,
A Learning Method for Definite Canonicalization Based on Minimum Classification Error,
ICPR00(Vol II: 199-202).
IEEE DOI Link
HTML Version. 0009
BibRef

Hansen, J.V., Heskes, T.,
General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of Distributions,
ICPR00(Vol II: 207-210).
IEEE DOI Link
HTML Version. 0009
BibRef

Maron, O.[Oded], Ratan, A.L.[Aparna L.],
Multiple-Instance Learning for Natural Scene Classification,
DARPA98(1031-1036). BibRef 9800

Jia, J., Abe, K.,
Clustering of Learning Images and Generation of Multiple Prototypes for Object Recognition,
MVA98(xx-yy). BibRef 9800

Kalkreuter, B.[Bjorn], Büker, U.[Ulrich],
Learning in an Active Hybrid Vision System,
ICPR98(Vol I: 178-181).
IEEE DOI Link 9808
BibRef

Shekhar, C.[Chandra], Burlina, P.[Philippe], Moisan, S.[Sabine],
Design of Self-Tuning IU Systems,
DARPA97(529-536). BibRef 9700

Takeuchi, Y.[Yutaka], Gros, P.[Patric], Hebert, M.[Martial], Ikeuchi, K.[Katsushi],
Visual Learning for Landmark Recognition,
DARPA97(1467-1474). BibRef 9700

Brooks, R.A., Grimson, W.E.L., Poggio, T., Koch, C., Sodini, C., Stein, L., Yang, W.,
A Trainable Modular Vision System,
DARPA97(1307-1314). BibRef 9700

Teller, A.[Astro], Veloso, M.[Manuela],
Evolutionary Learning for Orchestration of a Signal-to-Symbol Mapper,
DARPA97(1475-1482). BibRef 9700

Borga, M.[Magnus], Knutsson, H.[Hans], and Landelinus, T.[Tomas],
Learning Canonical Correlations,
SCIA97(xx-yy) 9705

HTML Version. BibRef

Chen, S.Y.[Shao-Yun], and Weng, J.[John],
On-Line Incremental Learning for Vision-Guided Real-Time Navigation Using Improved Updating,
SCIA97(xx-yy) 9705

HTML Version. BibRef
Earlier: A2, A1:
Incremental Learning for Vision-Based Navigation,
ICPR96(IV: 45-49).
IEEE DOI Link 9608
(Michigan State Univ., USA) BibRef

Thirion, E., Quan, L.,
Geometrical Learning from Multiple Stereo Views Through Monocular Based Feature Grouping,
ICCV90(481-484).
IEEE DOI Link BibRef 9000

Chao, J., Nakayama, J.,
Cubical Singular Simplex Model for 3D Objects and Fast Computation of Homology Groups,
ICPR96(IV: 190-194).
IEEE DOI Link 9608
(Chuo Univ., J) BibRef

Zanardi, C., Herve, J.Y., Cohen, P.,
Mutual Learning of Unsupervised Interactions Between Mobile Robots,
ICPR96(IV: 40-44).
IEEE DOI Link 9608
(Ecole Polytechnique de Montreal, CDN) BibRef

Burge, M., Mayr, W., Burger, W.,
Recognition and Learning With Polymorphic Structural Components,
ICPR96(I: 19-23).
IEEE DOI Link 9608
(Johannes Kepler Univ., A) BibRef

Sajda, P., Spence, C.D., Pearson, J.D.,
Learning Image Context for Improved Computer-Aided Diagnosis,
ARPA96(1375-1380). BibRef 9600

Zheng, Y.J., Bhanu, B.,
Adaptive Object Detection Based on Modified Hebbian Learning,
ICPR96(IV: 164-168).
IEEE DOI Link 9608
BibRef
And:
Performance Improvement by Input Adaption Using Modified Hebbian Learning,
ARPA96(1381-1388). (Univ. of California, Riverside, USA) BibRef

Rong, S., Bhanu, B.,
Reinforcement Learning for Integrating Context with Clutter Models for Target Detection,
ARPA96(1389-1394). ATR. BibRef 9600

Narenthiran, N., Boult, T.E.,
Color Channel Mixing in Learning from Appearance,
ARPA96(1455-1456). BibRef 9600

Bhanu, B.[Bir], and Dutta, R.[Rabi],
A Learning System for Consolidated Recognition and Motion Analysis,
ARPA94(I:773-776). BibRef 9400

Khuller, S.[Samir], Rivlin, E.[Ehud], and Rosenfeld, A.[Azriel],
Learning to Navigate on a Graph,
ARPA94(I:789-795). BibRef 9400

Jovanovic, L.,
Learning Algorithm Based on Modified Structure of Pattern Classes,
ICPR92(I:487-490).
IEEE DOI Link BibRef 9200

Valev, V., Radeva, P.I.,
A method of solving pattern or image recognition problems by learning Boolean formulas,
ICPR92(II:359-362).
IEEE DOI Link 9208
BibRef

Soloway, E.M., Riseman, E.M.,
Levels of Pattern Description in Learning,
IJCAI77(801-811).Cp

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Learning, General Surveys, Overviews .

Last update:Nov 16, 2009 at 19:35:14