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Recognition of mortar pumpability via computer vision and deep learning

Hao-Zhe Feng Hong-Yang Yu Wen-Yong Wang Wen-Xuan Wang Ming-Qian Du

电子科技学刊2023，Vol.21Issue(3)：73-81,9.

电子科技学刊2023，Vol.21Issue(3)：73-81,9.DOI:10.1016/j.jnlest.2023.100215

Recognition of mortar pumpability via computer vision and deep learning

Hao-Zhe Feng ¹Hong-Yang Yu ¹Wen-Yong Wang ²Wen-Xuan Wang ²Ming-Qian Du³

作者信息

1. Research Institute Electronic Science and Technology,University of Electronic Science and Technology of China,Chengdu,611731,China
2. School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu,611731,China
3. The Second Research Institute of Civil Aviation Administration of China,Chengdu,610041,China
折叠

摘要

关键词

Classification/Computer vision/Deep learning/Pumpability/2-dimensional convolutional long short-term memory network (ConvLSTM2D)/3-dimensional convolutional neural network(3D CNN)

Key words

Classification/Computer vision/Deep learning/Pumpability/2-dimensional convolutional long short-term memory network (ConvLSTM2D)/3-dimensional convolutional neural network(3D CNN)

引用本文复制引用

Hao-Zhe Feng,Hong-Yang Yu,Wen-Yong Wang,Wen-Xuan Wang,Ming-Qian Du..Recognition of mortar pumpability via computer vision and deep learning[J].电子科技学刊,2023,21(3):73-81,9.

基金项目

This work was supported by the Key Project of National Natural Science Foundation of China-Civil Aviation Joint Fund under Grant No.U2033212 （）

电子科技学刊

OACSCD

ISSN：1674-862X

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