Feature-Selection High-Resolution Network With Hypersphere Embedding for Semantic Segmentation of VHR Remote Sensing Images-Reference-Cited by-同舟云学术

Feature-Selection High-Resolution Network With Hypersphere Embedding for Semantic Segmentation of VHR Remote Sensing Images

Author:

Xu Hanwen¹^ORCID,Tang Xinming²,Ai Bo¹^ORCID,Yang Fanlin¹^ORCID,Wen Zhen¹,Yang Xiaomeng¹^ORCID

Affiliation:

1. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China

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

Funder

Key Program of the National Natural Science Foundation of China

General Program of the National Natural Science Foundation of China

Open Fund of the Key Laboratory of Urban Natural Resources Monitoring and Simulation, Ministry of Natural Resources

Shandong University of Science and Technology (SDUST) Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference69 articles.

2. Multi-scale dense networks for resource efficient image classification;huang;arXiv 1703 09844,2017

5. Semantic image segmentation with deep convolutional nets and fully connected CRFs;chen;arXiv 1412 7062,2014

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