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Deep Learning, Image Segmentation, AI for Science
China

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Employment (2)

Central South University: Changsha, Hunan, CN

2019-09-01 to 2023-06-30 | Master Student (Key Laboratory of Traffic Safety on Track)
Employment
Source: Self-asserted source
Zhaoyang Li

Central South University: Changsha, Hunan, CN

2019-09-01 to 2023-06-30 | Master Student (Joint International Research Laboratory of Key Technology for Rail Traffic Safety)
Employment
Source: Self-asserted source
Zhaoyang Li

Education and qualifications (2)

Central South University: Changsha, Hunan, CN

2019-09-01 to 2023-06-30 | Master (School of Traffic and Transportation Engineering)
Education
Source: Self-asserted source
Zhaoyang Li

Central South University: Changsha, Hunan, CN

2015-09-01 to 2019-06-30 | Bachelor (School of Traffic and Transportation Engineering)
Education
Source: Self-asserted source
Zhaoyang Li

Works (5)

Recognition and optimisation method of impact deformation patterns based on point cloud and deep clustering: Applied to thin-walled tubes

Journal of Industrial Information Integration
2024-07 | Journal article
Contributors: Chengxing Yang; Zhaoyang Li; Ping Xu; Huichao Huang
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Prediction method of impact deformation mode based on multimodal fusion with point cloud sequences: Applied to thin-walled structures

Advanced Engineering Informatics
2024-01 | Journal article
Contributors: Chengxing Yang; Zhaoyang Li; Ping Xu; Huichao Huang; Yujia Huo; Yuyang Wei
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SDFormer: A Novel Transformer Neural Network for Structural Damage Identification by Segmenting the Strain Field Map

Which Factors Contribute to Innovative Performance? A Case Study Applied to the Food and Beverage Industry
2022-04-07 | Book chapter
Part of ISBN: 9789392117466
Contributors: Chengxing Yang; Zhaoyang Li; Ping Xu; Jie Xing
Source: Self-asserted source
Zhaoyang Li
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SDFormer: A Novel Transformer Neural Network for Structural Damage Identification by Segmenting the Strain Field Map

Sensors
2022-03-18 | Journal article
Contributors: Zhaoyang Li; Ping Xu; Jie Xing; Chengxing Yang
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A Novel Bearing Fault Classification Method Based on XGBoost: The Fusion of Deep Learning-Based Features and Empirical Features

IEEE Transactions on Instrumentation and Measurement
2021 | Journal article
Contributors: Jingsong Xie; Zhaoyang Li; Zitong Zhou; Scarlett Liu
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