Fetching the paper…
Reading the bibliography…
The fundamental challenge in SAR target detection lies in developing discriminative, efficient, and robust representations of target characteristics within intricate non-cooperative environments.
R. E. Kalman, A new approach to linear filtering and prediction problems, Trans.ASME (1960) 35–44
1960
Earlier work this paper cites.
H. M. Finn, Adaptive detection in clutter, in: Fifth Symposium on Adaptive Processes, IEEE, 1966, pp. 562–567
1966
Earlier work this paper cites.
F. HM, Adaptive detection mode with threshold control as a function of spatially sampled clutter-level estimates, Rca Rev. 29 (1968) 414–465
1968
Earlier work this paper cites.
L. M. Novak, G. J. Owirka, C. M. Netishen, Performance of a high-resolution polarimetric SAR automatic target recognition system, Lincoln Laboratory Journal 6 (1) (1993)
1993
Earlier work this paper cites.
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, C. L. Zitnick, Microsoft COCO: Common objects in context, in: Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13, Springer, 2014, pp. 740–755
2014
Earlier work this paper cites.
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, S. Ganguli, Deep unsupervised learning using nonequilibrium thermodynamics, in: International Conference on Machine Learning, PMLR, 2015, pp. 2256–2265
2015
Earlier work this paper cites.
S. Ren, K. He, R. Girshick, J. Sun, Faster R-CNN: Towards real-time object detection with region proposal networks, IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (6) (2016) 1137–1149
2016
Earlier work this paper cites.
J. Li, C. Qu, J. Shao, Ship detection in SAR images based on an improved Faster R-CNN, in: 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA), IEEE, 2017, pp. 1–6
2017
Earlier work this paper cites.
T.-Y. Lin, P. Goyal, R. Girshick, K. He, P. Dollár, Focal loss for dense object detection, in: Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 2980–2988
2017
Earlier work this paper cites.
L. Huang, B. Liu, B. Li, W. Guo, W. Yu, Z. Zhang, W. Yu, OpenSARShip: A dataset dedicated to Sentinel-1 ship interpretation, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 (1) (2017) 195–208
2017
Earlier work this paper cites.
S. Elfwing, E. Uchibe, K. Doya, Sigmoid-weighted linear units for neural network function approximation in reinforcement learning, Neural networks 107 (2018) 3–11
2018
Earlier work this paper cites.
J. Redmon, A. Farhadi, Yolov3: An incremental improvement, arXiv preprint arXiv:1804.02767 (2018)
2018
Earlier work this paper cites.
Y. Wang, C. Wang, H. Zhang, Y. Dong, S. Wei, A SAR dataset of ship detection for deep learning under complex backgrounds, Remote Sensing 11 (7) (2019) 765
2019
Earlier work this paper cites.
Z. Cai, N. Vasconcelos, Cascade R-CNN: High quality object detection and instance segmentation, IEEE Transactions on pattern analysis and machine intelligence 43 (5) (2019) 1483–1498
2019
Earlier work this paper cites.
K. Duan, S. Bai, L. Xie, H. Qi, Q. Huang, Q. Tian, Centernet: Keypoint triplets for object detection, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019, pp. 6569–6578
2019
Earlier work this paper cites.
Z. Yang, S. Liu, H. Hu, L. Wang, S. Lin, Reppoints: Point set representation for object detection, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019, pp. 9657–9666
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
S. Xian, W. Zhirui, S. Yuanrui, D. Wenhui, Z. Yue, F. Kun, AIR-SARShip-1.0: High-resolution SAR ship detection dataset, Journal of Radars 8 (6) (2019) 852–863
2019
Earlier work this paper cites.
L. Liu, W. Ouyang, X. Wang, P. Fieguth, J. Chen, X. Liu, M. Pietikäinen, Deep learning for generic object detection: A survey, International journal of computer vision 128 (2020) 261–318
2020
Earlier work this paper cites.
S. Wei, X. Zeng, Q. Qu, M. Wang, H. Su, J. Shi, HRSID: A high-resolution SAR images dataset for ship detection and instance segmentation, IEEE Access 8 (2020) 120234–120254
2020
Earlier work this paper cites.
J. Ho, A. Jain, P. Abbeel, Denoising Diffusion Probabilistic Models, Advances in neural information processing systems 33 (2020) 6840–6851
2020
Earlier work this paper cites.
doi:10.5281/zenodo.3908559
G. Jocher, Ultralytics YOLOv5 (2020) · 2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
X. Hou, W. Ao, Q. Song, J. Lai, H. Wang, F. Xu, FUSAR-Ship: Building a high-resolution SAR-AIS matchup dataset of Gaofen-3 for ship detection and recognition, Science China Information Sciences 63 (2020) 1–19
2020
Earlier work this paper cites.
2021
Earlier work this paper cites.
2021
Earlier work this paper cites.
T. Zhang, X. Zhang, J. Li, X. Xu, B. Wang, X. Zhan, Y. Xu, X. Ke, T. Zeng, H. Su, et al., SAR Ship Detection Dataset (SSDD): Official release and comprehensive data analysis, Remote Sensing 13 (18) (2021) 3690
2021
Earlier work this paper cites.
2021
Cited alongside, same era.
K. Fu, J. Fu, Z. Wang, X. Sun, Scattering-keypoint-guided network for oriented ship detection in high-resolution and large-scale SAR images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (2021) 11162–11178
2021
Cited alongside, same era.
Y. Hu, Y. Li, Z. Pan, A dual-polarimetric SAR ship detection dataset and a memory-augmented autoencoder-based detection method, Sensors 21 (24) (2021) 8478
2021
Cited alongside, same era.
I. G. Rizaev, O. Karakuş, S. J. Hogan, A. Achim, Modeling and SAR imaging of the sea surface: A review of the state-of-the-art with simulations, ISPRS Journal of Photogrammetry and Remote Sensing 187 (2022) 120–140
2022
Cited alongside, same era.
C.-Q. Zhang, Y. Deng, M.-Z. Chong, Z.-W. Zhang, Y.-H. Tan, Entropy-Based re-sampling method on SAR class imbalance target detection, ISPRS Journal of Photogrammetry and Remote Sensing 209 (2024) 432–447
2024
Closest in time.
Z. Cui, L. Mou, Z. Zhou, K. Tang, Z. Yang, Z. Cao, J. Yang, Feature Joint Learning for SAR Target Recognition, IEEE Transactions on Geoscience and Remote Sensing (2024)
2024
Closest in time.
Z. Huang, C. Wu, X. Yao, Z. Zhao, X. Huang, J. Han, Physics inspired hybrid attention for SAR target recognition, ISPRS Journal of Photogrammetry and Remote Sensing 207 (2024) 164–174
2024
Closest in time.
J. Lv, D. Zhu, Z. Geng, S. Han, Y. Wang, Z. Ye, T. Zhou, H. Chen, J. Huang, Recognition for SAR deformation military target from a new MiniSAR dataset using multi-view joint transformer approach, ISPRS Journal of Photogrammetry and Remote Sensing 210 (2024) 180–197
2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Y. Deng, D. Guan, Y. Chen, W. Yuan, J. Ji, M. Wei, SAR-ShipNet: SAR-Ship detection neural network via bidirectional coordinate attention and multi-resolution feature fusion, in: ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2022, pp. 3973–3977
2022
Cited alongside, same era.
S. Yang, W. An, S. Li, G. Wei, B. Zou, An improved FCOS method for ship detection in SAR images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 (2022) 8910–8927
2022
Cited alongside, same era.
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, B. Ommer, High-resolution image synthesis with latent diffusion models, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2022, pp. 10684–10695
2022
Cited alongside, same era.
P. Zhang, H. Xu, T. Tian, P. Gao, L. Li, T. Zhao, N. Zhang, J. Tian, SEFEPNet: Scale expansion and feature enhancement pyramid network for SAR aircraft detection with small sample dataset, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 (2022) 3365–3375
2022
Cited alongside, same era.
R. M. Asiyabi, A. Ghorbanian, S. N. Tameh, M. Amani, S. Jin, A. Mohammadzadeh, Synthetic aperture radar (SAR) for ocean: A review, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023)
2023
Cited alongside, same era.
G. Cheng, X. Yuan, X. Yao, K. Yan, Q. Zeng, X. Xie, J. Han, Towards large-scale small object detection: Survey and benchmarks, IEEE Transactions on Pattern Analysis and Machine Intelligence (2023)
2023
Cited alongside, same era.
W. Zhirui, K. Yuzhuo, Z. Xuan, W. Yuelei, Z. Ting, S. Xian, SAR-AIRcraft-1.0: High-resolution SAR aircraft detection and recognition dataset, Journal of Radars 12 (4) (2023) 906–922
2023
Cited alongside, same era.
S. Chen, P. Sun, Y. Song, P. Luo, DiffusionDet: Diffusion model for object detection, in: Proceedings of the IEEE/CVF international conference on computer vision, 2023, pp. 19830–19843
2023
Cited alongside, same era.
J. Li, J. Chen, C. Xu, Z. Yu, L. Yu, P. Cheng, A Lightweight SAR Ship Detector Based on Whole Process Collaborative Designing, IEEE Transactions on Aerospace and Electronic Systems (2024)
2024
Closest in time.
L. Ying, Y. Liu, Z. Zhang, D. Miao, Multi-granularity-aware network for SAR ship detection in complex backgrounds, IEEE Geoscience and Remote Sensing Letters (2024)
2024
Closest in time.
K. Li, D. Wang, Z. Hu, W. Zhu, S. Li, Q. Wang, Unleashing channel potential: space-frequency selection convolution for SAR object detection, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 17323–17332
2024
Closest in time.
Z. Chen, T. Liu, X. Xu, J. Leng, Z. Chen, DCTC: Fast and Accurate Contour-Based Instance Segmentation with DCT Encoding for high resolution remote sensing images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024)
2024
Closest in time.
H. Lin, J. Liu, X. Li, L. Wei, Y. Liu, B. Han, Z. Wu, DCEA: DETR With Concentrated Deformable Attention for End-to-End Ship Detection in SAR Images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024)
2024
Closest in time.
C. Li, Y. Hei, L. Xi, W. Li, Z. Xiao, GL-DETR: Global-to-Local Transformers for Small Ship Detection in SAR Images, IEEE Geoscience and Remote Sensing Letters (2024)
2024
Closest in time.
J. Zhou, C. Xiao, B. Peng, Z. Liu, L. Liu, Y. Liu, X. Li, DiffDet4SAR: Diffusion-based aircraft target detection network for SAR images, IEEE Geoscience and Remote Sensing Letters (2024)
2024
Closest in time.
K. Wu, Z. Zhang, Z. Chen, G. Liu, Object-enhanced YOLO networks for synthetic aperture radar ship detection, Remote Sensing 16 (6) (2024) 1001
2024
Closest in time.
B. Kolbeinsson, K. Mikolajczyk, Multi-class segmentation from aerial views using recursive noise diffusion, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024, pp. 8439–8449
2024
Closest in time.
S. Shen, Z. Zhu, L. Fan, H. Zhang, X. Wu, DiffCLIP: Leveraging stable diffusion for language grounded 3D classification, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024, pp. 3596–3605
2024
Closest in time.
D. Qosja, S. Wagner, D. O’Hagan, SAR Image Synthesis with Diffusion Models, in: 2024 IEEE Radar Conference (RadarConf24), IEEE, 2024, pp. 1–6
2024
Closest in time.
X. Hu, Z. Xu, Z. Chen, Z. Feng, M. Zhu, L. Stanković, SAR despeckling via regional denoising diffusion probabilistic model, in: IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2024, pp. 7226–7230
2024
Closest in time.
Z. Guo, J. Liu, Q. Cai, Z. Zhang, S. Mei, Learning SAR-to-Optical Image Translation via Diffusion Models with Color Memory, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024)
2024
Closest in time.
S. Gou, X. Wang, X. Wang, Y. Chen, Interpretable Matching of Optical-SAR Image via Dynamically Conditioned Diffusion Models, in: ACM Multimedia 2024, 2024
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
K. Chen, B. Chen, C. Liu, W. Li, Z. Zou, Z. Shi, Rsmamba: Remote sensing image classification with state space model, IEEE Geoscience and Remote Sensing Letters (2024)
2024
Closest in time.
X. Ma, X. Zhang, M.-O. Pun, RS3Mamba: visual state space model for remote sensing image semantic segmentation, IEEE Geoscience and Remote Sensing Letters (2024)
2024
Closest in time.
2024
Closest in time.