Fault Detection For Automatic Guided Vehicles Based on The Two-tower Model-Reference-Cited by-同舟云学术

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Fault Detection For Automatic Guided Vehicles Based on The Two-tower Model

Published:2022-04-15 Issue: Volume: Page:
ISSN:
Container-title:2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP)
language:
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Author:

Ding Xiaohu¹,Zhang Dongdong¹,Zhang Liangang²,Zhang Lei²,Zhang Changjiang³,Xu Bin⁴

Affiliation:

1. Tongji University,Department of Computer Science,Shanghai,China

2. Qingdao Port International Co., Ltd,Technology Center,Qingdao,China

3. Qingdao Port International Co., Ltd,New Qianwan Container Terminal,Qingdao,China

4. Qingdao Port International Co., Ltd,Corporate Management,Qingdao,China

Funder

Ministry of Science and Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9778230/9778231/09778758.pdf?arnumber=9778758

Reference10 articles.

1. Anomaly Detection in Automated Vehicles Using Multistage Attention-Based Convolutional Neural Network

2. One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes

3. Sampling-bias-corrected neural modeling for large corpus item recommendations

4. An SVM-Based Solution for Fault Detection in Wind Turbines

5. A Novel Fault Detection, Identification and Prediction Approach for Autonomous Vehicle Controllers Using SVM. Automot;biddle;Innovation,2021

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