no code implementations • 31 Aug 2023 • Chenwei Wang, Xiaoyu Liu, Yulin Huang, Siyi Luo, Jifang Pei, Jianyu Yang, Deqing Mao
The recognition performance of 94. 18\% can be achieved under 20 training samples in each class with simultaneous accurate segmentation results.
1 code implementation • 20 Aug 2023 • Chenwei Wang, Siyi Luo, Jifang Pei, Yulin Huang, Yin Zhang, Jianyu Yang
Based on the initial recognition results, the feature capture module automatically searches and locks the crucial image regions for correct recognition, which we named as the golden key of image.
no code implementations • 20 Aug 2023 • Chenwei Wang, Siyi Luo, Yulin Huang, Jifang Pei, Yin Zhang, Jianyu Yang
The designed augmenter increases the amount of information available for supervised training and improves the separability of the extracted features.
no code implementations • 20 Aug 2023 • Chenwei Wang, Siyi Luo, Jifang Pei, Xiaoyu Liu, Yulin Huang, Yin Zhang, Jianyu Yang
In this letter, we propose an entropy-awareness meta-learning method that improves the exclusiveness of feature distribution of known classes which means our method is effective for not only classifying the seen classes but also encountering the unseen other classes.
no code implementations • 20 Aug 2023 • Chenwei Wang, Siyi Luo, Jifang Pei, Yulin Huang, Yin Zhang, Jianyu Yang
However, the characteristics of SAR ship images, large inner-class variance, and small interclass difference lead to the whole features containing useless partial features and a single feature center for each class in the classifier failing with large inner-class variance.
no code implementations • 20 Aug 2023 • Chenwei Wang, Jifang Pei, Siyi Luo, Weibo Huo, Yulin Huang, Yin Zhang, Jianyu Yang
Therefore, we proposed a SAR ship recognition method via multi-scale feature attention and adaptive-weighted classifier to enhance features in each scale, and adaptively choose the effective feature scale for accurate recognition.
1 code implementation • 18 Aug 2023 • Chenwei Wang, You Qin, Li Li, Siyi Luo, Yulin Huang, Jifang Pei, Yin Zhang, Jianyu Yang
As a result, it has a detrimental causal effect damaging the efficacy of feature $X$ extracted from SAR images, leading to weak generalization of SAR ATR with limited data.
no code implementations • 18 Aug 2023 • Chenwei Wang, Xin Chen, You Qin, Siyi Luo, Yulin Huang, Jifang Pei, Jianyu Yang
Then, a feature discrimination approach with hybrid similarity measurement is introduced to measure and mitigate the structural and vector angle impacts of varying imaging conditions on the extracted features from SAR images.
no code implementations • 15 Aug 2023 • Chenwei Wang, Jifang Pei, Yulin Huang, Jianyu Yang
In this paper, we proposed a deep deformable residual learning network for target segmentation that attempts to preserve the precise contour of the target.
no code implementations • 14 Aug 2023 • Chenwei Wang, Jifang Pei, Zhiyong Wang, Yulin Huang, Junjie Wu, Haiguang Yang, Jianyu Yang
In this paper, we propose a new multi-task learning approach for SAR ATR, which could obtain the accurate category and precise shape of the targets simultaneously.
no code implementations • 10 Aug 2023 • Chenwei Wang, Jifang Pei, Xiaoyu Liu, Yulin Huang, Deqing Mao, Yin Zhang, Jianyu Yang
The similarity discriminator can differentiate the generated SAR target images from the real SAR images to ensure the accuracy of the generated, while the azimuth predictor measures the difference of azimuth between the generated and the desired to ensure the azimuth controllability of the generated.
no code implementations • 10 Aug 2023 • Chenwei Wang, Yulin Huang, Xiaoyu Liu, Jifang Pei, Yin Zhang, Jianyu Yang
Convolutional neural networks (CNNs) have dominated the synthetic aperture radar (SAR) automatic target recognition (ATR) for years.
1 code implementation • 27 Jun 2023 • Chenwei Wang, Siyi Luo, Lin Liu, Yin Zhang, Jifang Pei, Yulin Huang, Jianyu Yang
In recent years, deep learning has been widely used to solve the bottleneck problem of synthetic aperture radar (SAR) automatic target recognition (ATR).
no code implementations • 29 Sep 2021 • Yu Tian, Chenwei Wang
We investigate the problem of wireless beam tracking on mmWave bands with the assistance of camera images.
1 code implementation • 6 Nov 2020 • YuAn Wang, Chenwei Wang, Yinan Ling, Keita Yokoyama, Hsin-Tai Wu, Yi Fang
Finally, we apply ESLE to seek new service ports for NTT DOCOMO's bike share services operated in Japan.