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

共 50 条

[41] Review of Deep Learning-Based Semantic Segmentation
Zhang Xiangfu
Jian, Liu
Shi Zhangsong
Wu Zhonghong
Zhi, Wang
[J]. LASER & OPTOELECTRONICS PROGRESS, 2019, 56 (15)
[42] Supervised semantic segmentation based on deep learning: a survey
Zhou, Yuguo
Ren, Yanbo
Xu, Erya
Liu, Shiliang
Zhou, Lijian
[J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (20) : 29283 - 29304
[43] Supervised semantic segmentation based on deep learning: a survey
Yuguo Zhou
Yanbo Ren
Erya Xu
Shiliang Liu
Lijian Zhou
[J]. Multimedia Tools and Applications, 2022, 81 : 29283 - 29304
[44] Weakly Supervised Semantic Segmentation Based on Deep Learning
Liang, Binxiu
Liu, Yan
He, Linxi
Li, Jiangyun
[J]. PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON MODELLING, IDENTIFICATION AND CONTROL (ICMIC2019), 2020, 582 : 455 - 464
[45] Overview of RGBD semantic segmentation based on deep learning
Zhang H.
Sheng V.S.
Xi X.
Cui Z.
Rong H.
[J]. Journal of Ambient Intelligence and Humanized Computing, 2023, 14 (10) : 13627 - 13645
[46] Meteorological Radar Noise Image Semantic Segmentation Method Based on Deep Convolutional Neural Network
Yang Hongyun
Wang Fengyan
[J]. JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2019, 41 (10) : 2373 - 2381
[47] Semantic Image Segmentation with Deep Features
Sunetci, Sercan
Ates, Hasan F.
[J]. 2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2018,
[48] One research on image semantic segmentation algorithms in deep learning networks
Lai, Shouliang
Zhang, Yichen
Wang, Meiyan
[J]. BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2019, 125 : 58 - 58
[49] RelationNet: Learning Deep-Aligned Representation for Semantic Image Segmentation
Zhuang, Yueqing
Tao, Li
Yang, Fan
Ma, Cong
Zhang, Ziwei
Jia, Huizhu
Xie, Xiaodong
[J]. 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2018, : 1506 - 1511
[50] Semantic Image Segmentation using Deep Learning for Low Illumination Environment
Sakhamuri, Sridevi
Kumar, K. Kiran
[J]. INTERNATIONAL JOURNAL OF EARLY CHILDHOOD SPECIAL EDUCATION, 2022, 14 (03) : 2452 - 2461

← 1 2 3 4 5 →