14.5 Learning in Computer Vision

Domke, J.[Justin], Karapurkar, A.[Alap], Aloimonos, Y.[Yiannis],
Who killed the directed model?,
CVPR08(1-8).
WWW Version. 0806MRF (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).
WWW Version. 0710 BibRef

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

Fu, Y.[Yun], Li, Z.[Zhu], Zhou, X.[Xi], Huang, T.S.[Thomas S.],
Laplacian Affinity Propagation for Semi-Supervised Object Classification,
ICIP07(I: 189-192).
WWW Version. 0709graph-based learning algorithm BibRef

Haro, G.[Gloria], Randall, G.[Gregory], Sapiro, G.[Guillermo],
Regularized Mixed Dimensionality and Density Learning in Computer Vision,
ComponentAnalysis07(1-8).
WWW Version. 0706 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

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

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

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

Xiong, H.[Huilin], Swamy, M.N.S., Ahmad, M.O.,
Learning with the Optimized Data-Dependent Kernel,
LCV04(95).
WWW Version. 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).
WWW Version. 0510 BibRef

Leitner, R.[Raimund],
Learning 3D Object Recognition from an Unlabelled and Unordered Training Set,
ISVC07(I: 644-651).
WWW Version. 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).
WWW Version. 0509 BibRef

Muńoz, X.[Xavier], Bosch, A.[Anna], Martí, J.[Joan], Espunya, J.[Joan],
A Learning Framework for Object Recognition on Image Understanding,
IbPRIA05(II:311).
WWW Version. 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).
WWW Version. 0409 BibRef

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

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

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

Eriksson, M.[Martin], Carlsson, S.[Stefan],
Qualitative Characterization and Use of Prior Information,
SCIA03(792-799).
WWW Version. 0310Model 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).
WWW Version. 0211 BibRef

Mizutani, H.[Hiroyuki],
Discriminative Learning for Minimum Error and Minimum Reject Classification,
ICPR98(Vol I: 136-140).
WWW Version. 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).
WWW Version. 0211 BibRef

Borga, M., Andersson, M., Knutsson, H.,
Generation of Representations for Supervised Learning: A Velocity Estimation Example,
SCIA01(O-W2). 0206 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).
WWW Version. 0709 BibRef
Earlier:
A Generalized Multiple Instance Learning Algorithm with Multiple Selection Strategies for Cross Granular Learning,
ICIP06(3213-3216). 0610
WWW Version. BibRef

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

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

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

Bala, J.W., Michalski, R.S., Wnek, J.,
The Prax Approach to Learning a Large Number of Texture Concepts,
AAAI-MLCV93(xx-yy). George Mason University. BibRef 9300

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).
WWW Version. 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).
WWW Version. 9608(Michigan State Univ., USA) BibRef

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

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

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

Burge, M., Mayr, W., Burger, W.,
Recognition and Learning With Polymorphic Structural Components,
ICPR96(I: 19-23).
WWW Version. 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).
WWW Version. 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).
WWW Version. BibRef 9200

Valev, V., Radeva, P.,
A method of solving pattern or image recognition problems by learning Boolean formulas,
ICPR92(II:359-362).
WWW Version. 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:Aug 16, 2008 at 14:24:48