Unsupervised Multi-level Segmentation Framework for PolSAR Data using H-Alpha features and the Combined Edge- Region based segmentation
Author:
Affiliation:
1. Military Technical College,Aircraft Electric System Department,Cairo,Egypt
2. National authoritie of remote sensing and space Sciences,Cairo,Egypt
3. Military Technical College,Cairo,Egypt
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10115529/10115530/10115863.pdf?arnumber=10115863
Reference17 articles.
1. A Lightweight Complex-Valued DeepLabv3+ for Semantic Segmentation of PolSAR Image
2. Semisupervised Classification of PolSAR Image Incorporating Labels’ Semantic Priors
3. Decomposition-Feature-Iterative-Clustering-Based Superpixel Segmentation for PolSAR Image Classification
4. SAR Image Matching Based on Local Feature Detection and Description Using Convolutional Neural Network
5. An Active Deep Learning Approach for Minimally Supervised PolSAR Image Classification
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Land cover analysis of PolSAR images using probabilistic voting ensemble and integrated support vector machine;Journal of Applied Remote Sensing;2023-10-20
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