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
Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review, CrossRef] 3. Tait, P. Introduction to Radar Target Recognition, pp.6014-6058, 2005. ,
DOI : 10.1109/ACCESS.2016.2611492
Hierarchical segmentation on ISAR image for target recongition, Int. J. Comput. Res, vol.5, pp.63-71, 2009. ,
Target recognition in SAR images using radial Chebyshev moments Signal Image Video Process Decision fusion based on physically relevant features for SAR ATR. IET Radar Sonar Navig ATR performance using enhanced resolution SAR, Algorithms for Synthetic Aperture Radar Imagery III; International Society for Optics and Photonics, pp.1033-1040, 1996. ,
Target Recognition in SAR Images Based on Information-Decoupled Representation. Remote Sens, p.138, 2018. ,
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
Thresholding in salient object detection: a survey, Multimedia Tools and Applications, 2017. ,
DOI : 10.1109/TIP.2015.2456497
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
A novel target detection method for SAR images based on shadow proposal and saliency analysis, Neurocomputing, vol.267, pp.220-231, 2017. ,
DOI : 10.1016/j.neucom.2017.06.004
Visual Attention-Based Target Detection and Discrimination for High-Resolution SAR Images in Complex Scenes, IEEE Transactions on Geoscience and Remote Sensing, vol.56, issue.4, pp.1855-1872, 2017. ,
DOI : 10.1109/TGRS.2017.2769045
Efficient Saliency-Based Object Detection in Remote Sensing Images Using Deep Belief Networks, IEEE Geoscience and Remote Sensing Letters, vol.13, issue.2, pp.137-141, 2016. ,
DOI : 10.1109/LGRS.2015.2498644
Sparse Representation-Based SAR Image Target Classification on the 10-Class MSTAR Data Set, Applied Sciences, vol.21, issue.1, p.26 ,
DOI : 10.1145/1961189.1961199
A Soft Decision Rule for Sparse Signal Modeling via Dempster???Shafer Evidential Reasoning, IEEE Geoscience and Remote Sensing Letters, vol.13, issue.10, pp.1567-1571, 2016. ,
DOI : 10.1109/LGRS.2016.2596301
SAR Target Recognition via Joint Sparse Representation of Monogenic Signal, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.8, issue.7, pp.3316-3328, 2015. ,
DOI : 10.1109/JSTARS.2015.2436694
Target Recognition in Radar Images Using Weighted Statistical Dictionary-Based Sparse Representation, IEEE Geoscience and Remote Sensing Letters, vol.14, issue.12, pp.2403-2407, 2017. ,
DOI : 10.1109/LGRS.2017.2766225
URL : https://hal.archives-ouvertes.fr/hal-01653569
Automatic Target Recognition of Military Vehicles With Krawtchouk Moments, IEEE Transactions on Aerospace and Electronic Systems, vol.53, issue.1, pp.493-500, 2017. ,
DOI : 10.1109/TAES.2017.2649160
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
Target classification using SIFT sequence scale invariants, Journal of Systems Engineering and Electronics, vol.23, issue.5, pp.633-639, 2012. ,
DOI : 10.1109/JSEE.2012.00079
Target detection in SAR images using SIFT, 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp.7-10, 2015. ,
DOI : 10.1109/ISSPIT.2015.7394426
Target detection in SAR images using SIFT, Proceedings of the 2017 IEEE International Conference on Advanced Technologies for Signal and Image Processing (ATSIP'2017), pp.22-24, 2017. ,
Fuzzy fusion system for radar target recognition, Int. J. Comput. Appl. Inf. Technol, vol.1, pp.136-142, 2012. ,
URL : https://hal.archives-ouvertes.fr/hal-00777095
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
Transfer Learning with Deep Convolutional Neural Network for SAR Target Classification with Limited Labeled Data, Remote Sensing, vol.9349, issue.9, p.907 ,
DOI : 10.1109/LGRS.2017.2698213
Deep Learning for target recognition from SAR images, 2017 Seminar on Detection Systems Architectures and Technologies (DAT), pp.20-22, 2017. ,
DOI : 10.1109/DAT.2017.7889171
URL : https://hal.archives-ouvertes.fr/hal-01656457
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
Deep Convolutional Highway Unit Network for SAR Target Classification With Limited Labeled Training Data, IEEE Geoscience and Remote Sensing Letters, vol.14, issue.7, pp.1091-1095, 2017. ,
DOI : 10.1109/LGRS.2017.2698213
Modern approaches in deep learning for SAR ATR, Algorithms for Synthetic Aperture Radar Imagery XXIII; International Society for Optics and Photonics, p.98430, 2016. ,
DOI : 10.1117/12.2220290
Robust Face Recognition via Sparse Representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.2, pp.210-227, 2009. ,
DOI : 10.1109/TPAMI.2008.79
URL : http://www.csee.wvu.edu/~xinl/courses/ee565/PAMIface.pdf
A survey on representation-based classification and detection in hyperspectral remote sensing imagery, Pattern Recognition Letters, vol.83, pp.115-123, 2016. ,
DOI : 10.1016/j.patrec.2015.09.010
Ship Classification in TerraSAR-X Images With Feature Space Based Sparse Representation, IEEE Geoscience and Remote Sensing Letters, vol.10, issue.6, pp.1562-1566, 2013. ,
DOI : 10.1109/LGRS.2013.2262073
Sparse representation-based synthetic aperture radar imaging. IET Radar Sonar Navig, pp.182-193, 2011. ,
DOI : 10.1049/iet-rsn.2009.0235
SAR Target Recognition via Local Sparse Representation of Multi-Manifold Regularized Low-Rank Approximation. Remote Sens, p.211, 2018. ,
A novel remote sensing image retrieval method based on visual salient point features, Sensor Review, vol.34, issue.4, pp.349-359, 2014. ,
DOI : 10.1109/LGRS.2009.2035644
Partial Face Recognition: Alignment-Free Approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.5, pp.1193-1205, 2013. ,
DOI : 10.1109/TPAMI.2012.191
URL : http://biometrics.cse.msu.edu/Publications/Face/LiaoJain_PartialFR_AlignmentFreeApproach_ICJB11.pdf
3D Face Recognition Based on Multiple Keypoint Descriptors and Sparse Representation, PLoS ONE, vol.31, issue.6 ,
DOI : 10.1371/journal.pone.0100120.t003
URL : https://doi.org/10.1371/journal.pone.0100120
Improved method for SAR image registration based on scale invariant feature transform. IET Radar Sonar Navig, pp.579-585, 2017. ,
Saliency-based multi-feature modeling for semantic image retrieval, Journal of Visual Communication and Image Representation, vol.50, pp.199-204, 2018. ,
DOI : 10.1016/j.jvcir.2017.11.021
URL : https://hal.archives-ouvertes.fr/hal-01671560
Hybrid-feature-guided lung nodule type classification on CT images, Computers & Graphics, vol.70, pp.288-299, 2018. ,
DOI : 10.1016/j.cag.2017.07.020
l1-Magic: Rrrecovery of Sparse Signals via Convex Programming, 2007. ,
RCS of Complex Targets: Original Representation Validated by Measurements-Application to ISAR Imagery This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http, Licensee MDPI, pp.3882-3891 ,