EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application.
Jiyong HuHongfei YangJiatang HeDongxu BaiHongda ChenPublished in: IEEE Access (2024)
Keyphrases
- highly accurate
- model driven
- high level
- neural network
- modeling method
- formal model
- statistical model
- computational model
- mathematical model
- experimental data
- bayesian framework
- similarity measure
- network model
- autoregressive
- real time
- defect detection
- high speed
- high accuracy
- probabilistic model
- conceptual model
- bayesian networks
- image processing
- capable of producing