SAR Image Segmentation with Superpixel Constraint and Fuzzy Clustering
Author:
Affiliation:
1. University of Electronic Science and Technology of China, China
2. 22nd Research Institute of China Electronics Technology Group Corporation, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3577117.3577136
Reference22 articles.
1. Shi X.; Zhou F.; Yang S.; Zhang Z.; Su T. 2019. Automatic Target Recognition for Synthetic Aperture Radar Images Based on Super-Resolution Generative Adversarial Network and Deep Convolutional Neural Network. Remote Sens. https://doi.org/10.3390/rs11020135 10.3390/rs11020135
2. Shi X.; Zhou F.; Yang S.; Zhang Z.; Su T. 2019. Automatic Target Recognition for Synthetic Aperture Radar Images Based on Super-Resolution Generative Adversarial Network and Deep Convolutional Neural Network. Remote Sens. https://doi.org/10.3390/rs11020135
3. A lossless lightweight CNN design for SAR target recognition
4. Monitoring of surface instability in tourist zones in Sanya (China) using high-resolution SAR interferometry;Tang P;Remote Sensing Letters,129-138. https://doi.org/10.1080/2150704X.,2019
5. . Two-Stage Cross-Modality Transfer Learning Method for Military-Civilian SAR Ship Recognition;Song Y;IEEE Geoscience and Remote Sensing Letters,2022
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