Lightweight Ship Recognition Algorithm Based on SNN in SAR Images
Hong-tu XIE1, Jia-xing CHEN1, Lin ZHANG2, Nan-nan ZHU3
1.School of Electronics and Communication Engineering，Shenzhen Campus of Sun Yat-sen University，Shenzhen 518107，China 2.Air Force Early Warning Academy，Wuhan 430019，China 3.School of Systems Science and Engineering，Sun Yat-sen University，Guangzhou 510275，China. Corresponding author： ZHU Nan-nan，E-mail： zhunn25@mail. sysu. edu. cn
Hong-tu XIE, Jia-xing CHEN, Lin ZHANG, Nan-nan ZHU. Lightweight Ship Recognition Algorithm Based on SNN in SAR Images[J]. Journal of Northeastern University(Natural Science), 2024, 45(4): 474-482.
Hu X， Xie H T， Zhang L，et al.Fast factorized backprojection algorithm in orthogonal elliptical coordinate system for ocean scenes imaging using geosynchronous spaceborne‐airborne VHF UWB bistatic SAR［J］.Remote Sensing，2023，15（8）：2215-2241.
2
Chen J X， Xie H T， Zhang L，et al.SAR and optical image registration based on deep learning with co‐attention matching module［J］.Remote Sensing，2023，15（15）：3879-3896.
3
Jiang X Q， Xie H T， Chen J X，et al.Arbitrary‐oriented ship detection method based on long‐edge decomposition rotated bounding box encoding in SAR images［J］.Remote Sensing，2023，15（3）：673-694.
4
Jiang X Q， Xie H T， Lu Z，et al.Energy‑efficient and high‑performance ship classification strategy based on siamese spiking neural network in dual‑polarized SAR images［J］.Remote Sensing，2023，15（20）：4966-4983.
5
Xie H T， He J F， Lu Z，et al.Two‐level feature‐fusion ship recognition strategy combining HOG features with dual‐polarized data in SAR images［J］.Remote Sensing，2023，15（18）：4393-4405.
6
Devlin J， Chang M W， Lee K，et al.BERT：pre‐training of deep bidirectional transformers for language understanding［C］//Conference of the North American Chapter of the Association for Computational Linguistics.Minneapolis，2019：4171-4186.
7
Brown T B， Mann B， Ryder N，et al.Language models are few‑shot learners［C］//International Conference on Neural Information Processing Systems.Vancouver，2020：1877-1901.
8
Fedus W， Zoph B， Shazeer N.Switch transformers：scaling to trillion parameter models with simple and efficient sparsity［J］.Journal of Machine Learning Research，2022，23：1-40.
9
Roy K， Jaiswal A， Panda P.Towards spike‐based machine intelligence with neuromorphic computing［J］.Nature，2019，575（7784）：607-617.
10
Hong C F， Yuan M W， Zhang M X，et al.SPAIC：a spike‐based artificial intelligence computing frame work［J］.IEEE Computational Intelligence Magazine，2024，19（1）：51-65.
11
Kim S， Park S， Na B，et al.Spiking‐YOLO：spiking neural network for energy‐efficient object detection［C］//AAAI Conference on Artificial Intelligence.New York，2020：11270-11277.
Li Chao， Li Yue‐li， An Dao‐xiang，et al.UWB SAR change detection of foliage‐concealed targets based on visual attention［J］.Acta Electronica Sinica，2016，44（1）：39-45.
13
Gerstner W， Kistler W， Naud R，et al.Neuronal dynamics：from single neurons to networks and models of cognition［M］.Cambridge：Cambridge University Press，2014.
14
Schwegmann C P， Kleynhans W， Salmon B P，et al.Very deep learning for ship discrimination in synthetic aperture radar imagery［C］//IEEE International Geoscience and Remote Sensing Symposium. Beijing，2016：104-107.
