A semi-supervised support vector machines approach for condition monitoring of construction equipment-Reference-Cited by-同舟云学术

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A semi-supervised support vector machines approach for condition monitoring of construction equipment

Published:2022-07-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)
language:
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Author:

Cao Shubo¹,Liu Shitao¹,Shi Yunfei¹,Pan Yubo¹,Han Lifang²,Yang Yiwei³

Affiliation:

1. The Second Construction Ltd Company of China Construction Eighth Engineering Division,Department of Information Center,Jinan,China,250014

2. China Construction Eighth Engineering Bureau Co., Ltd.,Shanghai,China,200122

3. Jinan Engineering Quality and Safety Center,Jinan,China,250102

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9872150/9872152/09872264.pdf?arnumber=9872264

Reference15 articles.

1. A robust semi-supervised SVM via ensemble learning

2. Log facies identification in carbonate reservoirs using multiclass semi-supervised learning strategy

3. Semi-supervised learning for medical image classification using imbalanced training data

4. Road damage detection using super-resolution and semi-supervised learning with generative adversarial network

5. Fuzziness based semi-supervised learning approach for intrusion detection system

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1. Trajectory tracking switching control system for autonomous crawler dump under varying ground condition;Automation in Construction;2023-04

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