A Mutual Information Domain Adaptation Network for Remotely Sensed Semantic Segmentation-Reference-Cited by-同舟云学术

A Mutual Information Domain Adaptation Network for Remotely Sensed Semantic Segmentation

Author:

Chen Hongyu¹^ORCID,Zhang Hongyan¹^ORCID,Yang Guangyi²^ORCID,Li Shengyang³^ORCID,Zhang Liangpei¹^ORCID

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

2. School of Electronic Information, Wuhan University, Wuhan, China

3. Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference62 articles.

1. Domain-adversarial training of neural networks;ganin;J Mach Learn Res,2016

3. IM2HEIGHT: Height estimation from single monocular imagery via fully residual convolutional-deconvolutional network;mou;arXiv 1802 10249,2018

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