Semantic image segmentation network based on deep learning

Bo Chen; Jiahao Zhang; Jianbang Zhou; Zhong Chen; Jian Yang; Yanna Zhang

doi:10.1117/12.2538067

14 February 2020 Semantic image segmentation network based on deep learning

Bo Chen, Jiahao Zhang, Jianbang Zhou, Zhong Chen, Jian Yang, Yanna Zhang

Proceedings Volume 11429, MIPPR 2019: Automatic Target Recognition and Navigation; 114290G (2020) https://doi.org/10.1117/12.2538067
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

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.

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Bo Chen, Jiahao Zhang, Jianbang Zhou, Zhong Chen, Jian Yang, and Yanna Zhang "Semantic image segmentation network based on deep learning", Proc. SPIE 11429, MIPPR 2019: Automatic Target Recognition and Navigation, 114290G (14 February 2020); https://doi.org/10.1117/12.2538067

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KEYWORDS

Image segmentation

Remote sensing

Vegetation

Computer programming

Roads

Buildings

Image analysis

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