A novel combined method for conveyor belt deviation discrimination under complex operational scenarios-Reference-Cited by-同舟云学术

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A novel combined method for conveyor belt deviation discrimination under complex operational scenarios

Published:2024-11 Issue: Volume:137 Page:109145
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Gao Mengze,Li Shihua,Chen Xisong,Wang Yongjian^ORCID

Funder

National Outstanding Youth Science Fund Project of National Natural Science Foundation of China

Alexander von Humboldt-Stiftung

Key Laboratory for the Synthesis and Application of Organic Functional Molecules, Ministry of Education

Southeast University

Publisher

Elsevier BV

Reference38 articles.

1. Application of a deep learning semantic segmentation model to helium bubbles and voids in nuclear materials;Agarwal;Eng. Appl. Artif. Intell.,2023

2. Attention mechanisms in computer vision: A survey;Guo;Comput. Vis. Media,2022

3. Spatial pyramid pooling in deep convolutional networks for visual recognition;He;IEEE Trans. Pattern Anal. Mach. Intell.,2015

4. Hu, J., Shen, L., Sun, G., 2018. Squeeze-and-excitation networks. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7132–7141.

5. Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., Matas, J., 2018. DeblurGAN: Blind motion deblurring using conditional adversarial networks. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8183–8192.

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