S. Sahli, Y. Ouyang, Y. Sheng, and D. A. Lavigne, Robust vehicle detection in low-resolution aerial imagery, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII, 2010.
DOI : 10.1117/12.850387

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.511-518, 2001.
DOI : 10.1109/CVPR.2001.990517

H. Meng, D. R. Hardoon, J. Shawe-taylor, and S. Szedmak, <title>Generic object recognition by combining distinct features in machine learning</title>, Applications of Neural Networks and Machine Learning in Image Processing IX, 2005.
DOI : 10.1117/12.585810

C. Szegedy, A. Toshev, and D. Erhan, Deep neural networks for object detection, Advances in Neural Information Processing Systems, pp.2553-2561, 2013.

D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov, Scalable Object Detection Using Deep Neural Networks, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.2155-2162, 2014.
DOI : 10.1109/CVPR.2014.276

K. Rong-en-fan, C. Chang, X. Hsieh, C. Wang, and . Lin, LIBLINEAR: A library for large linear classification, Journal of Machine Learning Research, vol.9, pp.1871-1874, 2008.

J. Gao and P. Ning-tan, Converting Output Scores from Outlier Detection Algorithms into Probability Estimates, Sixth International Conference on Data Mining (ICDM'06), pp.212-221, 2006.
DOI : 10.1109/ICDM.2006.43

A. Krizhevsky, S. Ilya, and G. E. Hinton, Imagenet classification with deep convolutional neural networks, Advances in Neural Information Processing Systems 25, pp.1097-1105, 2012.

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

Q. Zhu, M. Yeh, K. Cheng, and S. Avidan, Fast human detection using a cascade of histograms of oriented gradients, Computer Vision and Pattern Recognition, pp.1491-1498, 2006.

S. Kim, S. Kavuri, and M. Lee, Deep Network with Support Vector Machines, Lecture Notes in Computer Science, vol.8226, pp.458-465, 2013.
DOI : 10.1007/978-3-642-42054-2_57

J. Pasquet, M. Chaumont, G. Subsol, and M. Derras, An efficient multi-resolution SVM network approach for object detection in aerial images, Machine Learning for signal processing, 2015.
URL : https://hal.archives-ouvertes.fr/lirmm-01234225

J. Pasquet, T. Desert, O. Bartoli, M. Chaumont, C. Delenne et al., Detection of manhole covers in high-resolution aerial images of urban areas by combining two methods, Joint Urban Remote Sensing Event (JURSE), 2015.
URL : https://hal.archives-ouvertes.fr/lirmm-01234242

M. Chaumont, L. Tribouillard, G. Subsol, F. Courtade, J. Pasquet et al., Automatic localization of tombs in aerial imagery: Application to the digital archiving of cemetery heritage, 2013 Digital Heritage International Congress (DigitalHeritage), pp.657-660, 2013.
DOI : 10.1109/DigitalHeritage.2013.6743811

URL : https://hal.archives-ouvertes.fr/lirmm-01234256

M. Anderson, S. Stokes, M. Motta, and R. Chandrasekar, Proposal for a standard default color space for the internet -sRGB, Proc. of IS&T and SID´sSID´s 4th Color Imaging Conference: Color Science , Systems and Applications, pp.238-246, 1996.

P. Ganesan, V. Rajini, and R. I. Rajkumar, Segmentation and edge detection of color images using CIELAB color space and edge detectors, INTERACT-2010, pp.393-397, 2010.
DOI : 10.1109/INTERACT.2010.5706186

G. Jeon, Measuring and Comparison of Edge Detectors in Color Spaces, International Journal of Control and Automation, vol.6, issue.5, pp.21-29, 2013.
DOI : 10.14257/ijca.2013.6.5.03

D. Aldavert, A. Ramisa, R. López-de-mántaras, and R. Toledo, Real-Time Object Segmentation using a Bag of Features Approach, 13th International Conference of the ACIA, L'Espluga de Francolí, 2010.

K. M. Ting and I. H. Witten, Stacked generalization: when does it work, Procs. International Joint Conference on Artificial Intelligence, pp.866-871, 1997.