A multi-label image classification method combining multi-stage image semantic information and label relevance-Reference-Cited by-同舟云学术

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A multi-label image classification method combining multi-stage image semantic information and label relevance

Published:2024-04-08 Issue:9 Volume:15 Page:3911-3925
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Wu Liwen,Zhao Lei,Tang Peigeng,Pu Bin,Jin Xin,Zhang Yudong,Yao Shaowen

Funder

Youth Project for Basic Research of Yunnan Province Science and Technology Department

Fundamental Research Funds for the Central Universities

Science and Technology Plan in Key Fields of Yunnan Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13042-024-02127-1.pdf

Reference45 articles.

1. Kordnoori S, Sabeti M, Mostafaei H (2023) Analysis of lung scan imaging using deep multi-task learning structure for Covid-19 disease. IET Image Process. https://doi.org/10.1049/ipr2.12736

2. Qian K, Chen P, Zhao D (2023) GOMT: multispectral video tracking based on geneticoptimization and multi-features integration. IET Image Process. https://doi.org/10.1049/ipr2.12739

3. Qiu Y, Wang Z-Q, Zhu P-C (2023) A multisensory-feedback tactile glove with dense coverage of sensing arrays for object recognition. Chem Eng J 455:140890. https://doi.org/10.1016/j.cej.2022.140890

4. Zhang W, Zhang X, Tang Y (2023) Facial expression recognition based on improvedresidual network. IET Image Process. https://doi.org/10.1049/ipr2.12743

5. Zhou W-J, Yue Y-C, Fang M-X (2023) BCINet: bilateral cross-modal interaction network for indoor scene understanding in RGB-D images. Inf Fusion 94:32–42. https://doi.org/10.1016/j.inffus.2023.01.016

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