Ke Yang Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
faculty
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Biography and Research Information
OverviewAI-generated summary
Ke Yang's research focuses on the application of advanced machine learning techniques, particularly deep convolutional neural networks, for intelligent fault diagnosis and predictive modeling. Yang has investigated novel principal component analysis methods integrated with long short-term memory networks for productivity prediction in areas such as cutter suction dredgers. Recent work includes the development of efficient convolutional neural networks for intelligent fault diagnosis and studies on chemical kinetic models for specific compounds like 1-methylnaphthalene. Yang's scholarly contributions are reflected in an h-index of 11 and over 1,800 citations across 26 publications. Collaborations include shared publications with Richard G. Ham and Richard J. Ham from the Arkansas Agricultural Experiment Station and Meijing Tan from the University of Arkansas at Fayetteville.
Metrics
- h-index: 11
- Publications: 26
- Citations: 1,815
Selected Publications
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An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems (2025)
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Analysis of Censored Aggregate Failure-time Data Using Phase-type Distributions (2025)
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Development of a Detailed Chemical Kinetic Model for 1-Methylnaphthalene (2024)
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Molecular Characterization and Expression Analysis of a Gene Encoding 3-Hydroxy-3-Methylglutaryl-CoA Reductase (HMGR) from Bipolaris eleusines, an Ophiobolin A-Producing Fungus (2024)
Collaboration Network
Top Collaborators
- Multi-Criteria Spare Parts Classification Using the Deep Convolutional Neural Network Method
- A transfer learning-based convolutional neural network and its novel application in ship spare-parts classification
- A Novel Principal Component Analysis Integrating Long Short-Term Memory Network and Its Application in Productivity Prediction of Cutter Suction Dredgers
- Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy
- A transfer learning-based convolutional neural network and its novel application in ship spare-parts classification
- Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy
- ECNN: Intelligent Fault Diagnosis Method Using Efficient Convolutional Neural Network
- Intelligent Fault Diagnosis Method through ACCC-Based Improved Convolutional Neural Network
- ECNN: Intelligent Fault Diagnosis Method Using Efficient Convolutional Neural Network
- Intelligent Fault Diagnosis Method through ACCC-Based Improved Convolutional Neural Network
- Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy
- An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems
- Analysis of Censored Aggregate Failure-time Data Using Phase-type Distributions
- An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems
- Multi-Criteria Spare Parts Classification Using the Deep Convolutional Neural Network Method
- Multi-Criteria Spare Parts Classification Using the Deep Convolutional Neural Network Method
- A Novel Principal Component Analysis Integrating Long Short-Term Memory Network and Its Application in Productivity Prediction of Cutter Suction Dredgers
- A Novel Principal Component Analysis Integrating Long Short-Term Memory Network and Its Application in Productivity Prediction of Cutter Suction Dredgers
- A Novel Principal Component Analysis Integrating Long Short-Term Memory Network and Its Application in Productivity Prediction of Cutter Suction Dredgers
- A transfer learning-based convolutional neural network and its novel application in ship spare-parts classification
- Recurring Clear Cell Odontogenic Carcinoma Involving Vertebra and Pleura: A Case Report and Literature Review
- Recurring Clear Cell Odontogenic Carcinoma Involving Vertebra and Pleura: A Case Report and Literature Review
- Recurring Clear Cell Odontogenic Carcinoma Involving Vertebra and Pleura: A Case Report and Literature Review
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