R. Veltkamp, A Survey of Content-Based Image Retrieval Systems, Tech. Rep, 2002.
DOI : 10.1007/978-1-4615-0987-5_5

Y. Rui, T. Huang, S. Mehrotra, and M. Ortega, A relevance feedback architecture for content-based multimedia information retrieval systems, IEEE Workshop on Content-Based Access of Image and Video Libraries, pp.92-89, 1997.

E. Chang, B. T. Li, G. Wu, and K. Goh, Statistical learning for effective visual information retrieval, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), pp.609-612, 2003.
DOI : 10.1109/ICIP.2003.1247318

S. Aksoy, R. Haralick, F. Cheikh, and M. Gabbouj, A weighted distance approach to relevance feedback, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, pp.812-815, 2000.
DOI : 10.1109/ICPR.2000.903041

J. Peng, B. Bhanu, and S. Qing, Probabilistic Feature Relevance Learning for Content-Based Image Retrieval, Computer Vision and Image Understanding, vol.75, issue.1-2, pp.150-164, 1999.
DOI : 10.1006/cviu.1999.0770

N. Doulamis and A. Doulamis, A recursive optimal relevance feedback scheme for cbir, International Conference in Image Processing (ICIP'01), 2001.

J. Fournier, M. Cord, and S. Philipp-foliguet, Back-propagation algorithm for relevance feedback in image retrieval, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), pp.686-689, 2001.
DOI : 10.1109/ICIP.2001.959138

O. Chapelle, P. Haffner, and V. Vapnik, Support vector machines for histogram-based image classification, IEEE Transactions on Neural Networks, vol.10, issue.5, pp.1055-1064, 1999.
DOI : 10.1109/72.788646

N. Vasconcelos, Bayesian models for visual information retrieval, 2000.

S. Berrani, L. Amsaleg, and P. Gros, Recherche approximative de plus proches voisins, Technique et Science Informatiques, pp.221201-1230, 2003.
DOI : 10.3166/tsi.22.1201-1230
URL : https://hal.archives-ouvertes.fr/inria-00604073

N. Najjar, J. Cocquerez, and C. Ambroise, Feature selection for semi supervised learning applied to image retrieval, IEEE ICIP, pp.559-562, 2003.

X. Zhu, Z. Ghahramani, and J. Lafferty, Semi-supervised learning using gaussian fields and harmonic functions, International Conference on Machine Learning, 2003.

]. A. Dong and B. Bhanu, Active Concept Learning in Image Databases, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.35, issue.3, pp.450-466, 2005.
DOI : 10.1109/TSMCB.2005.846653

N. Vasconcelos and M. Kunt, Content-based retrieval from image databases: current solutions and future directions, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), pp.6-9, 2001.
DOI : 10.1109/ICIP.2001.958037

Y. Chen, X. Zhou, and T. Huang, One-class svm for learning in image retrieval, International Conference in Image Processing (ICIP), pp.34-37, 2001.

S. Berrani, L. Amsaleg, and P. Gros, Approximate searches: kneighbors + precision, International Conference on Information and Knowledge Management, pp.24-31, 2003.
DOI : 10.1145/956863.956870

V. Vapnik, Statistical Learning Theory, 1998.

S. Tong and D. Koller, Support vector machine active learning with application to text classification, Journal of Machine Learning Research, issue.2, pp.45-66, 2001.

S. Mika, G. Rätsch, J. Weston, B. Schölkopf, K. Müller et al., Fisher discriminant analysis with kernels, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468), pp.41-48, 1999.
DOI : 10.1109/NNSP.1999.788121

P. Yin, B. Bhanu, K. Chang, and A. Dong, Integrating relevance feedback techniques for image retrieval using reinforcement learning, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.27, pp.1536-1551, 2005.

J. Shawe-taylor and N. Cristianini, Kernel methods for Pattern Analysis, 2004.
DOI : 10.1017/CBO9780511809682

T. Joachims, Transductive inference for text classification using support vector machines, Proc. 16th International Conference on Machine Learning, pp.200-209, 1999.

P. Gosselin, M. Najjar, M. Cord, and C. Ambroise, Discriminative classification vs modeling methods in CBIR, IEEE Advanced Concepts for Intelligent Vision Systems (ACIVS), 2004.
URL : https://hal.archives-ouvertes.fr/hal-00520316

P. Gosselin and M. Cord, Retin al: an active learning strategy for image category retrieval, 2004 International Conference on Image Processing, 2004. ICIP '04., pp.2219-2222, 2004.
DOI : 10.1109/ICIP.2004.1421538
URL : https://hal.archives-ouvertes.fr/hal-00520315

N. Roy and A. Mccallum, Toward optimal active learning through sampling estimation of error reduction, International Conference on Machine Learning, 2001.

D. Cohn, Active learning with statistical models, Journal of Artificial Intelligence Research, vol.4, pp.129-145, 1996.

D. D. Lewis and J. Catlett, Heterogeneous uncertainly sampling for supervised learning, International Conference on Machine Learning, pp.148-56, 1994.

J. M. Park, Online learning by active sampling using orthogonal decision support vectors, IEEE Workshop on Neural Networks for Signal Processing, pp.263-283, 2000.

M. Lindenbaum, S. Markovitch, and D. Rusakov, Selective Sampling for Nearest Neighbor Classifiers, Machine Learning, pp.54125-152, 2004.
DOI : 10.1023/B:MACH.0000011805.60520.fe

I. Cox, M. Miller, T. Minka, T. Papathomas, and P. Yianilos, The Bayesian image retrieval system, PicHunter: theory, implementation, and psychophysical experiments, IEEE Transactions on Image Processing, vol.9, issue.1, pp.20-37, 2000.
DOI : 10.1109/83.817596

D. Geman and R. Moquet, A stochastic feedback model for image retrieval, RFIA'2000, pp.173-180, 2000.

S. Tong and E. Chang, Support vector machine active learning for image retrieval, Proceedings of the ninth ACM international conference on Multimedia , MULTIMEDIA '01, pp.107-118, 2001.
DOI : 10.1145/500141.500159

P. Gosselin and M. Cord, A comparison of active classification methods for content-based image retrieval, Proceedings of the 1st international workshop on Computer vision meets databases , CVDB '04, 2004.
DOI : 10.1145/1039470.1039483
URL : https://hal.archives-ouvertes.fr/hal-00520318

M. Cord, P. Gosselin, and S. Philipp-foliguet, Stochastic exploration and active learning for image retrieval, Image and Vision Computing, vol.25, issue.1, pp.14-23, 2006.
DOI : 10.1016/j.imavis.2006.01.004
URL : https://hal.archives-ouvertes.fr/hal-00520289

K. Brinker, Incorporating diversity in active learning with support vector machines, International Conference on Machine Learning, pp.59-66, 2003.