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

doi:10.1007/s00371-023-02954-3

	HTCViT: an effective network for image classification and segmentation based on natural disaster datasets
	Ma, Zhihao 1,3; Li, Wei1,3 ; Zhang, Muyang 1,3; Meng, Weiliang1,2,3 ; Xu, Shibiao4 ; Zhang, Xiaopeng1,2,3
发表期刊	VISUAL COMPUTER
ISSN	0178-2789
	2023-07-04
页码	13
通讯作者	Meng, Weiliang(weiliang.meng@ia.ac.cn) ; Xu, Shibiao(shibiaoxu@bupt.edu.cn)
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.
关键词	Natural disaster image analysis Vision transformer Convolution Hierarchical
DOI	10.1007/s00371-023-02954-3
收录类别	SCI
语种	英语
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]
项目资助者	National Natural Science Foundation of China ; Open Research Projects of ZhejiangLab
WOS研究方向	Computer Science
WOS类目	Computer Science, Software Engineering
WOS记录号	WOS:001025049000002
出版者	SPRINGER
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53649
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.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 2.Zhejiang Lab, Hangzhou, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing, Peoples R China 4.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
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.