D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94

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), 2005.
DOI : 10.1109/CVPR.2005.177

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

J. Wang, J. Yang, K. Yu, F. Lv, T. Huang et al., Locality-constrained Linear Coding for image classification, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5540018

L. Bo, X. Ren, and D. Fox, Kernel descriptors for visual recognition, pp.Vancou- ver, 2010.

H. Lobel, R. Vidal, and A. Soto, Hierarchical Joint Max-Margin Learning of Mid and Top Level Representations for Visual Recognition, 2013 IEEE International Conference on Computer Vision, 2013.
DOI : 10.1109/ICCV.2013.213

Y. Bengio, A. Courville, and P. Vincent, Representation Learning: A Review and New Perspectives, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.8, pp.1798-1828, 2013.
DOI : 10.1109/TPAMI.2013.50

K. Yu, Y. Lin, and J. Lafferty, Learning image representations from the pixel level via hierarchical sparse coding, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995732

Q. Le, M. Ranzato, R. Monga, M. Devin, K. Chan et al., Building high-level features using large scale unsupervised learning, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2012.
DOI : 10.1109/ICASSP.2013.6639343

H. Lee, R. Grosse, R. Ranganath, and A. Ng, Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009.
DOI : 10.1145/1553374.1553453

S. Lawrence, C. Giles, A. Tsoi, and D. Back, Face recognition: a convolutional neural-network approach, IEEE Transactions on Neural Networks, vol.8, issue.1, pp.98-113, 1997.
DOI : 10.1109/72.554195

R. Socher, B. Huval, B. Bhat, D. Manning, and A. Ng, Convolutional-recursive deep learning for 3D object classification, 2012.

A. Krizhevsky, I. Sutskever, and G. Hinton, ImageNet classification with deep convolutional neural networks, 2012.

L. Bo, X. Ren, and D. Fox, Multipath Sparse Coding Using Hierarchical Matching Pursuit, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.91

K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. Lecun, What is the best multi-stage architecture for object recognition?, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459469

T. Serre, L. Wolf, and T. Poggio, Object Recognition with Features Inspired by Visual Cortex, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.254

K. Kavukcuoglu, M. Ranzato, and Y. Lecun, Fast inference in sparse coding algorithm with applications to object recognition, 2008.

A. Saxe, P. Koh, Z. Chen, M. Bhand, B. Suresh et al., On random weights and unsupervised feature learning, 2011.

R. Socher, C. Maning, and A. Ng, Learning continuous phrase representation and syntactic parsing with recursive neural networks, In: NIPS, 2010.

S. Lazebnik, C. Schmid, and J. Ponce, Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.68

URL : https://hal.archives-ouvertes.fr/inria-00548585

N. Pinto, D. Cox, and J. Dicarlo, Why is Real-World Visual Object Recognition Hard?, PLoS Computational Biology, vol.58, issue.1, 2008.
DOI : 10.1371/journal.pcbi.0040027.sg004

A. Coates and A. Ng, The importance of encoding versus training with sparse coding and vector quantization, 2011.

H. Zhang, A. Berg, M. Maire, and J. Malik, SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.301

K. Kavukcuoglu, M. Ranzato, R. Fergus, and Y. Lecun, Learning invariant features through topographic filter maps, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
DOI : 10.1109/CVPR.2009.5206545