Semantic image segmentation network based on deep learning

被引：0

作者：

Chen, Bo ^{[1
]}

Zhang, Jiahao ^{[1
]}

Zhou, Jianbang ^{[1
]}

Chen, Zhong ^{[1
]}

Yang, Tian ^{[2
]}

Zhang, Yanna ^{[3
]}

机构：

[1] Huazhong Univ Sci & Technol, Inst Artificial Intelligence & Automat, Natl Key Lab Sci & Technol Multispectral Informat, Wuhan, Hubei, Peoples R China

[2] Chinese Acad Sci, Inst Aerosp Informat Innovat, Beijing, Peoples R China

[3] Henan Univ, Dept Lab & Equipment Management, Kaifeng, Henan, Peoples R China

来源：

MIPPR 2019: AUTOMATIC TARGET RECOGNITION AND NAVIGATION | 2020年 / 11429卷

关键词：

Semantic Segmentation; Attention Seg-Net; Deep Learning; Attention gate;

D O I：

10.1117/12.2538067

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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.

引用

页数：5

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