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HTCViT: an effective network for image classification and segmentation based on natural disaster datasets

文献类型：期刊论文

作者Ma, Zhihao2,4; Li, Wei2,4; Zhang, Muyang2,4; Meng, Weiliang2,3,4; Xu, Shibiao1; Zhang, Xiaopeng2,3,4
刊名VISUAL COMPUTER
出版日期2023-07-04
页码13
关键词Natural disaster image analysis Vision transformer Convolution Hierarchical
ISSN号0178-2789
DOI10.1007/s00371-023-02954-3
通讯作者Meng, Weiliang(weiliang.meng@ia.ac.cn) ; Xu, Shibiao(shibiaoxu@bupt.edu.cn)
英文摘要Classifying and segmenting natural disaster images are crucial for predicting and responding to disasters. However, current convolutional networks perform poorly in processing natural disaster images, and there are few proprietary networks for this task. To address the varying scales of the region of interest (ROI) in these images, we propose the Hierarchical TSAM-CB-ViT (HTCViT) network, which builds on the ViT network's attention mechanism to better process natural disaster images. Considering that ViT excels at extracting global context but struggles with local features, our method combines the strengths of ViT and convolution, and can capture overall contextual information within each patch using the Triple-Strip Attention Mechanism (TSAM) structure. Experiments validate that our HTCViT can improve the classification task with 3 - 4% and the segmentation task with 1 - 2% on natural disaster datasets compared to the vanilla ViT network.
资助项目National Natural Science Foundation of China[U21A20515] ; National Natural Science Foundation of China[61972459] ; National Natural Science Foundation of China[62172416] ; National Natural Science Foundation of China[62102414] ; National Natural Science Foundation of China[U2003109] ; National Natural Science Foundation of China[62071157] ; National Natural Science Foundation of China[62171321] ; National Natural Science Foundation of China[62162044] ; Open Research Projects of ZhejiangLab[2021KE0AB07] ; [TC210H00L/42]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001025049000002
出版者SPRINGER
资助机构National Natural Science Foundation of China ; Open Research Projects of ZhejiangLab
源URL[http://ir.ia.ac.cn/handle/173211/53648]  
专题多模态人工智能系统全国重点实验室
通讯作者Meng, Weiliang; Xu, Shibiao
作者单位1.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
3.Zhejiang Lab, Hangzhou, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Ma, Zhihao,Li, Wei,Zhang, Muyang,et al. HTCViT: an effective network for image classification and segmentation based on natural disaster datasets[J]. VISUAL COMPUTER,2023:13.
APA Ma, Zhihao,Li, Wei,Zhang, Muyang,Meng, Weiliang,Xu, Shibiao,&Zhang, Xiaopeng.(2023).HTCViT: an effective network for image classification and segmentation based on natural disaster datasets.VISUAL COMPUTER,13.
MLA Ma, Zhihao,et al."HTCViT: an effective network for image classification and segmentation based on natural disaster datasets".VISUAL COMPUTER (2023):13.

入库方式： OAI收割

来源：自动化研究所

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