Water-Body Type Classification in Dual PolSAR Imagery Using a Two-Step Deep-Learning Method

Author:

Yuan Qiming1ORCID,Lu Jing2ORCID,Wu Lin1ORCID,Huang Yabo1ORCID,Guo Zhengwei1ORCID,Li Ning1ORCID

Affiliation:

1. School of Computer and Information Engineering, Henan University, Kaifeng, China

2. Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing, China

Funder

Plan of Science and Technology of Henan Province

Key R&D Project of Science and Technology of Kaifeng City

Key Laboratory of Natural Resources Monitoring and Regulation in Southern Hilly Region

Ministry of Natural Resources of the People's Republic of China

Key Laboratory of Land Satellite Remote Sensing Application

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Cited by 2 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. Emerging methodologies in waterbody delineation: an In-depth review;International Journal of Remote Sensing;2024-07-31

2. Integrating Sparrow Search Algorithm with Deep Learning for Tomato Fruit Disease Detection and Classification;2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN);2024-05-03

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