Dual Attention-Based Industrial Surface Defect Detection with Consistency Loss
In industrial production, flaws and defects inevitably appear on surfaces, resulting in unqualified products. Therefore, surface defect detection plays a key role in ensuring industrial product quality and maintaining industrial production lines. However, surface defects on different products have d...
Main Authors: | Xuyang Li, Yu Zheng, Bei Chen, Enrang Zheng |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-07-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/14/5141 |
Similar Items
-
Industrial Product Surface Anomaly Detection with Realistic Synthetic Anomalies Based on Defect Map Prediction
by: Tao Peng, et al.
Published: (2024-01-01) -
An Attention-Augmented Convolutional Neural Network With Focal Loss for Mixed-Type Wafer Defect Classification
by: Uzma Batool, et al.
Published: (2023-01-01) -
OASIS-Net: Morphological Attention Ensemble Learning for Surface Defect Detection
by: Younggi Hong, et al.
Published: (2022-11-01) -
Adaptive rotation attention network for accurate defect detection on magnetic tile surface
by: Fang Luo, et al.
Published: (2023-09-01) -
Surface Defect Detection of Hot Rolled Steel Based on Attention Mechanism and Dilated Convolution for Industrial Robots
by: Yuanfan Yu, et al.
Published: (2023-04-01)