BSSNet: Building Subclass Segmentation From Satellite Images Using Boundary Guidance and Contrastive Learning

Author:

Xie Haofeng1ORCID,Hu Xiangyun1ORCID,Jiang Huiwei2ORCID,Zhang Jinming3ORCID

Affiliation:

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

2. National Geomatics Center of China, Beijing, China

3. Key Laboratory of Network Information System Technology, Institute of Electronic, and The Aerospace Information Research Institute, Chinese Academic of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Special Fund of Hubei Luojia Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Reference57 articles.

1. Exploring Cross-Image Pixel Contrast for Semantic Segmentation

2. Supervised contrastive learning;khosla;Adv Neural Inf Process Syst,2020

3. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models;gutmann;Proc 13th Int Conf Artif Intell Statis JMLR Workshop Conf Proc,0

4. Conditional image generation with pixelcnn decoders;oord;Advances in neural information processing systems,2016

5. Information constraints on auto-encoding variational bayes;lopez;Adv Neural Inf Process Syst,2018

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