D. Chenoweth, B. Cooper, and J. Selvage, Aerial image analysis using fractal-based models, 1995 IEEE Aerospace Applications Conference. Proceedings, 1995.
DOI : 10.1109/AERO.1995.468935

C. Unsalan and K. L. Boyer, Classifying land development in highresolution satellite imagery using hybrid structuralmultispectral features, IEEE Trans. on Geoscience and Remote Sensing, vol.42, issue.12, 2004.

A. Lorette, X. Descombes, and J. Zerubia, Texture analysis through a markovian modelling and fuzzy classification: Application to urban area extraction from satellite images, International Journal of Computer Vision, vol.36, issue.3, 2000.

S. Kumar and M. Hebert, Man-made structure detection in natural images using a causal multiscale random field, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., pp.119-126, 2003.
DOI : 10.1109/CVPR.2003.1211345

G. Mountrakis, J. Im, and C. Ogole, Support vector machines in remote sensing: A review, ISPRS Journal of Photogrammetry and Remote Sensing, vol.66, issue.3, pp.247-259, 2011.
DOI : 10.1016/j.isprsjprs.2010.11.001

M. Schröder, H. Rehrauer, K. Seidel, and M. Datcu, Interactive learning and probabilistic retrieval in remote sensing image archives, IEEE Transactions on Geoscience and Remote Sensing, vol.38, issue.5, pp.2288-2298, 2000.
DOI : 10.1109/36.868886

L. Bruzzone and C. Persello, Active learning for classification of remote sensing images, Proc. of International Geoscience and Remote Sensing Symposium, Cape Town, 2009.

D. Tuia, F. Ratle, F. Pacifici, M. Kanevski, and W. Emery, Active Learning Methods for Remote Sensing Image Classification, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.7, pp.2218-2232, 2009.
DOI : 10.1109/TGRS.2008.2010404

M. Molinier, J. Laaksonen, and T. Häme, Detecting Man-Made Structures and Changes in Satellite Imagery With a Content-Based Information Retrieval System Built on Self-Organizing Maps, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.4, pp.861-874, 2007.
DOI : 10.1109/TGRS.2006.890580

K. Koperski, G. Marchisio, S. Aksoy, and S. Tusk, VisiMine: interactive mining in image databases, IEEE International Geoscience and Remote Sensing Symposium, pp.1810-1812, 2002.
DOI : 10.1109/IGARSS.2002.1026262

M. Ferecatu and N. Boujemaa, Interactive Remote-Sensing Image Retrieval Using Active Relevance Feedback, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.4, pp.818-826, 2007.
DOI : 10.1109/TGRS.2007.892007

N. Chauffert, J. Israël, and B. L. Saux, Boosting for interactive man-made structure classification, 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012.
DOI : 10.1109/IGARSS.2012.6352588

Y. Freund and R. E. Schapire, A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Journal of Computer and System Sciences, vol.55, issue.1, 1997.
DOI : 10.1006/jcss.1997.1504

T. T. Nguyen, H. Grabner, B. Gruber, and H. Bischof, On-line Boosting for Car Detection from Aerial Images, 2007 IEEE International Conference on Research, Innovation and Vision for the Future, pp.87-95, 2007.
DOI : 10.1109/RIVF.2007.369140

L. Mason, J. Baxter, P. Bartlett, and M. Frean, Boosting algorithms as gradient descent, Advances in Neural Information Processing Systems, pp.512-518, 2000.

C. Leistner, A. Saffari, P. Roth, and H. Bischof, On robustness of online boosting -a competitive study, Proceedings of ICCV Workshop on On-line Learning for Computer Vision, 2009.

P. Long and R. Servedio, Random classification noise defeats all convex potential boosters, Machine Learning, pp.287-304, 2010.

A. Bordes and L. Bottou, The Huller: A Simple and Efficient Online SVM, Machine Learning: ECML, pp.505-512, 2005.
DOI : 10.1007/11564096_48

URL : https://hal.archives-ouvertes.fr/hal-00752501

B. Catanzaro, N. Sundaram, and K. Keutzer, Fast support vector machine training and classification on graphics processors, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.104-111, 2008.
DOI : 10.1145/1390156.1390170

K. Veropoulos, C. Campbell, and N. Christianini, Controlling the sensitivity of support vector machines, Proc. of the International Joint Conference on AI, pp.55-60, 1999.

X. Perrotton, M. Sturzel, and M. Roux, Automatic Object Detection on Aerial Images Using Local Descriptors and Image Synthesis, Proc. of International Conference on Vision Systems, 2008.
DOI : 10.1007/978-3-540-79547-6_29

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.886-893, 2005.
DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

L. Bruzzone and D. Prieto, Automatic analysis of the difference image for unsupervised change detection, IEEE Transactions on Geoscience and Remote Sensing, vol.38, issue.3, pp.1171-1182, 2000.
DOI : 10.1109/36.843009

B. , L. Saux, and H. Randrianarivo, Urban change detection in SAR images by interactive learning, Proc. of International Geoscience and Remote Sensing Symposium, 2013.

P. Lombardo and C. Oliver, Maximum likelihood approach to the detection of changes between multitemporal SAR images, IEE Proceedings - Radar, Sonar and Navigation, vol.148, issue.4, pp.200-210, 2001.
DOI : 10.1049/ip-rsn:20010114

B. , L. Saux, and M. Sanfourche, Rapid semantic mapping: Learn environment classifiers on the fly, Proc. of International Conference on Intelligent Robots and Systems, 2013.