A. Toumi, A. Khenchaf, and B. Hoeltzener, A retrieval system from inverse synthetic aperture radar images: Application to radar target recognition, Information Sciences, vol.196, pp.73-96, 2012.
DOI : 10.1016/j.ins.2012.01.049

URL : https://hal.archives-ouvertes.fr/hal-00738796

A. Karine, A. Toumi, A. Khenchaf, and M. E. Hassouni, Visual salient sift keypoints descriptors for automatic target recognition, 2016 6th European Workshop on Visual Information Processing (EUVIP), 2016.
DOI : 10.1109/EUVIP.2016.7764596

URL : https://hal.archives-ouvertes.fr/hal-01406143

Q. Zhao and J. C. Principe, Support vector machines for SAR automatic target recognition, IEEE Transactions on Aerospace and Electronic Systems, vol.37, issue.2, pp.643-654, 2001.
DOI : 10.1109/7.937475

Y. Sun, Z. Liu, S. Todorovic, and J. Li, Adaptive boosting for SAR automatic target recognition, IEEE Transactions on Aerospace and Electronic Systems, vol.43, issue.1, pp.112-125, 2007.
DOI : 10.1109/TAES.2007.357120

C. Tison, N. Pourthie, and J. C. Souyris, Target recognition in SAR images with Support Vector Machines (SVM), 2007 IEEE International Geoscience and Remote Sensing Symposium, pp.456-459, 2007.
DOI : 10.1109/IGARSS.2007.4422829

U. Srinivas, V. Monga, and R. G. Raj, Meta-classifiers for exploiting feature dependencies in automatic target recognition, 2011 IEEE RadarCon (RADAR), pp.147-151, 2011.
DOI : 10.1109/RADAR.2011.5960517

A. Agrawal, P. Mangalraj, and M. A. , Target detection in SAR images using SIFT, 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp.90-94, 2015.
DOI : 10.1109/ISSPIT.2015.7394426

A. Karine, A. Toumi, A. Khenchaf, and M. E. Hassouni, A non-Gaussian statistical modeling of SIFT and DT-CWT for radar target recognition, 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), 2016.
DOI : 10.1109/AICCSA.2016.7945648

URL : https://hal.archives-ouvertes.fr/hal-01406126

H. Song, K. Ji, Y. Zhang, X. Xing, and H. Zou, Sparse Representation-Based SAR Image Target Classification on the 10-Class MSTAR Data Set, Applied Sciences, vol.21, issue.1, p.26, 2016.
DOI : 10.1145/1961189.1961199

A. Housseini, A. Toumi, and A. Khenchaf, Deep Learning for target recognition from SAR images, 2017 Seminar on Detection Systems Architectures and Technologies (DAT), 2017.
DOI : 10.1109/DAT.2017.7889171

URL : https://hal.archives-ouvertes.fr/hal-01656457

S. Chen, H. Wang, F. Xu, and Y. Q. Jin, Target Classification Using the Deep Convolutional Networks for SAR Images, IEEE Transactions on Geoscience and Remote Sensing, vol.54, issue.8, pp.4806-4817, 2016.
DOI : 10.1109/TGRS.2016.2551720

C. Geng and X. Jiang, Face recognition using sift features, 2009 16th IEEE International Conference on Image Processing (ICIP), pp.3313-3316, 2009.
DOI : 10.1109/ICIP.2009.5413956

F. Dellinger, J. Delon, Y. Gousseau, J. Michel, and F. Tupin, SAR-SIFT: A SIFT-Like Algorithm for SAR Images, IEEE Transactions on Geoscience and Remote Sensing, vol.53, issue.1, pp.453-466, 2015.
DOI : 10.1109/TGRS.2014.2323552

URL : https://hal.archives-ouvertes.fr/hal-00831763

L. Itti, C. Koch, and E. Niebur, A model of saliency-based visual attention for rapid scene analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.11, pp.1254-1259, 1998.
DOI : 10.1109/34.730558

A. Borji and L. Itti, State-of-the-Art in Visual Attention Modeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.1, pp.185-207, 2013.
DOI : 10.1109/TPAMI.2012.89

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

URL : http://www.cs.ubc.ca/~lowe/papers/ijcv03.ps

E. R. Keydel, S. W. Lee, and J. T. Moore, MSTAR extended operating conditions: a tutorial, Aerospace/Defense Sensing and Controls. International Society for Optics and Photonics, pp.228-242, 1996.
DOI : 10.1117/12.242059

A. Karine, N. Lasmar, A. Baussard, and M. E. Hasosuni, Sonar image segmentation based on statistical modeling of wavelet subbands, 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA), 2015.
DOI : 10.1109/AICCSA.2015.7507134

URL : https://hal.archives-ouvertes.fr/hal-01266488