Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020 /
This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber P...
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| 企业作者: | |
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| 其他作者: | , , |
| 格式: | 电子 电子书 |
| 语言: | 英语 |
| 出版: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer Vieweg,
2021.
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| 版: | 1st ed. 2021. |
| 丛编: | Technologien für die intelligente Automation, Technologies for Intelligent Automation,
13 |
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| 在线阅读: | Link to Metadata |
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书本目录:
- Preface
- Energy Profile Prediction of Milling Processes Using Machine Learning Techniques
- Improvement of the prediction quality of electrical load profiles with artficial neural networks
- Detection and localization of an underwater docking station
- Deployment architecture for the local delivery of ML-Models to the industrial shop floor
- Deep Learning in Resource and Data Constrained Edge Computing Systems
- Prediction of Batch Processes Runtime Applying Dynamic Time Warping and Survival Analysis
- Proposal for requirements on industrial AI solutions
- Information modeling and knowledge extraction for machine learning applications in industrial production systems
- Explanation Framework for Intrusion Detection
- Automatic Generation of Improvement Suggestions for Legacy, PLC Controlled Manufacturing Equipment Utilizing Machine Learning
- Hardening Deep Neural Networks in Condition Monitoring Systems against Adversarial ExampleAttacks
- First Approaches to Automatically Diagnose and Reconfigure Hybrid Cyber-Physical Systems
- Machine learning for reconstruction of highly porous structures from FIB-SEM nano-tomographic data.