Bending Strength Prediction of the Cu-Sn Alloy Through a Visual Quantization Model Integrated With Microstructure Characterization and Machine Learning

Authors

• Wang, Longjian;
• Yu, Jianwu;
• Huang, Liang;
• Qian, Jun; 34150;
• Luo, Hong;

Publication Date

Jan 01, 2024

Source

Lirias

Keywords

• Science & Technology
• Technology
• Computer Science, Information Systems
• Engineering, Electrical & Electronic
• Telecommunications
• Computer Science
• Engineering
• Bending
• Wheels
• Microstructure
• Metals
• Heating Systems
• Diamonds
• Sintering
• Machine Learning
• Grinding Machines
• Performance Evaluation
• Bending Strength Prediction
• Cu-Sn Alloy
• Grinding Wheel
• Machine Learning
• Microscopic Feature
• Mechanical-Properties
• Fractal Dimension
• Grinding Wheels
• U-Net
• Performance
• Fabrication
• Tools
• Size

License

Unknown

External links

• Full record on lirias.kuleuven.be
  
• Full record on lirias.kuleuven.be