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Proceedings Paper

Semantic image segmentation network based on deep learning
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Paper Abstract

Semantic segmentation is one of the basic themes in computer vision. Its purpose is to assign semantic tags to each pixel of an image, which has been applied in many fields such as medical field, intelligent transportation and remote sensing image. In this paper, we use deep learning to solve the task of remote sensing semantic image segmentation. We propose an algorithm for semantic segmentation of the Attention Seg-Net network combined with SegNet and attention gate. Our proposed network can better segment vegetation, buildings, water bodies and roads in the test set of remote sensing images.

Paper Details

Date Published: 14 February 2020
PDF: 5 pages
Proc. SPIE 11429, MIPPR 2019: Automatic Target Recognition and Navigation, 114290G (14 February 2020); doi: 10.1117/12.2538067
Show Author Affiliations
Bo Chen, Huazhong Univ. of Science and Technology (China)
Jiahao Zhang, Huazhong Univ. of Science and Technology (China)
Jianbang Zhou, Huazhong Univ. of Science and Technology (China)
Zhong Chen, Huazhong Univ. of Science and Technology (China)
Jian Yang, Institute of Aerospace Information Innovation (China)
Yanna Zhang, Henan Univ. (China)


Published in SPIE Proceedings Vol. 11429:
MIPPR 2019: Automatic Target Recognition and Navigation
Jianguo Liu; Hanyu Hong; Xia Hua, Editor(s)

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