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NTIS 바로가기韓國軍事科學技術學會誌 = Journal of the KIMST, v.24 no.2, 2021년, pp.175 - 186
박지훈 (국방과학연구소 제3기술연구본부) , 서승모 (국방과학연구소 제3기술연구본부) , 유지희 (국방과학연구소 제3기술연구본부)
In the field of automatic target recognition(ATR) with synthetic aperture radar(SAR) imagery, it is usually impractical to obtain SAR target images covering a full range of aspect views. When the database consists of SAR target images with limited angular diversity, it can lead to performance degrad...
K. El-Darymli, et al., "Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review," IEEE Access, Vol. 6, pp. 6014-6058, 2016.
M. David, "Deep Convolutional Neural Networks for ATR from SAR Imagery," Proc. SPIE, Algorithms for Synthetic Aperture Radar Imagery XXII, Vol. 9475, 2015.
J. Ding, et al., "Convolutional Neural Network with Data Augmentation for SAR Target Recognition," IEEE Geoscience and Remote Sensing Letters, Vol. 13, No. 3, pp. 364-368, 2016.
S. Chen, et al., "Target Classification Using the Deep Convolutional Networks for SAR Images," IEEE Trans. Geoscience and Remote Sensing, Vol. 54, No. 8, pp. 4806-4817, 2016.
S. Wagner, "SAR ATR by Combination of Convolutional Neural Network and Support Vector Machine," IEEE Trans. Aerospace and Electronic Systems, Vol. 52, No. 6, pp. 2861-2872, 2016.
O. Kechagias-Stamatis et al., "Fusing Deep Learning and Sparse Coding for SAR ATR," IEEE Trans. Aerospace and Electronic Systems, Vol. 55, No. 2, pp. 785-797, 2019.
J. H. Cho, et al., "Multiple Feature Aggregation Using Convolutional Neural Networks for SAR Image-Based Automatic Target Recognition," IEEE Geoscience and Remote Sensing Letters, Vol. 15, No. 12, pp. 1882-1886, 2018.
Q. Yu, et al., "High-Performance SAR ATR Under Limited Data Condition Based on a Deep Feature Fusion Network," IEEE Access, Vol. 7, pp. 165646-165658, 2019.
Z. Lin, et al., "Deep Convolutional Highway Unit Network for SAR Target Classification with Limited Labeled Training Data," IEEE Geoscience and Remote Sensing Letters, Vol. 14, No. 7, pp. 1091-1095, 2017.
F. Zhou, et al., "SAR ATR of Ground Vehicles Based on LM-BN-CNN," IEEE Trans. Geoscience and Remote Sensing, Vol. 56, No. 12, pp. 7282-7293, 2018.
L. Wang, et al., "SAR ATR of Ground Vehicles Based on ESENet," Remote Sensing, Vol. 11, No. 11, pp. 1316-1331, 2019.
G. Huang, et al., "A Novel Group Squeeze Excitation Sparsely Connected Convolutional Networks for SAR Target Classification," International Journal of Remote Sensing, Vol. 40, No. 11, pp. 4346-4360, 2019.
F. Zhang, et al., "Multi-Aspect-Aware Bidirectional LSTM Networks for Synthetic Aperture Radar Target Recognition," IEEE Access, Vol. 5, pp. 26880-26891, 2017.
J. Pei, et al., "SAR Automatic Target Recognition Based on Multiview Deep Learning Framework," IEEE Trans. Geoscience and Remote Sensing, Vol. 56, No. 4, pp. 2196-2210, 2018.
P. Zhao, et al., "Multi-Stream Convolutional Neural Network for SAR Automatic Target Recognition," Remote Sensing Vol. 10, No. 9, pp. 1473-1494, 2018.
J. Hu, et al., "Squeeze-and-Excitation Networks," Proc. IEEE Conference on Computer Vision and Pattern Recognition(CVPR 2018), pp. 7132-7141, 2018.
K. He, et al., "Deep Residual Learning for Image Recognition," Proc. IEEE Conference on Computer Vision and Pattern Recognition(CVPR 2016), pp. 770-778, 2016.
K. He, et al., "Identity Mappings in Deep Residual Networks," Proc. European Conference in Computer Vision(ECCV 2016), pp. 630-645, 2016.
A. Bochkovskiy, et al., "YOLOv4 : Optimal Sped and Accuracy of Object Detection," arXiv 2020, Available Online:Arxiv.org/abs/2004.10934.
S. Woo, et al., "CBAM : Convolutional Block Attention Module," Proc. European Conference in Computer Vision(ECCV 2018), pp. 3-9, 2018.
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