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TrustMAE: A Noise-Resilient Defect Classification Framework using
  Memory-Augmented Auto-Encoders with Trust Regions

TrustMAE: A Noise-Resilient Defect Classification Framework using Memory-Augmented Auto-Encoders with Trust Regions

29 December 2020
Daniel Stanley Tan
Yi-Chun Chen
Trista Pei-chun Chen
Wei-Chao Chen
    UQCV
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Papers citing "TrustMAE: A Noise-Resilient Defect Classification Framework using Memory-Augmented Auto-Encoders with Trust Regions"

4 / 4 papers shown
Title
IPAD: Industrial Process Anomaly Detection Dataset
IPAD: Industrial Process Anomaly Detection Dataset
Jinfan Liu
Yichao Yan
Junjie Li
Weiming Zhao
Pengzhi Chu
Xingdong Sheng
Yunhui Liu
Xiaokang Yang
35
0
0
23 Apr 2024
SCL-VI: Self-supervised Context Learning for Visual Inspection of
  Industrial Defects
SCL-VI: Self-supervised Context Learning for Visual Inspection of Industrial Defects
Peng Wang
Haiming Yao
Wenyong Yu
8
3
0
11 Nov 2023
Diversity-Measurable Anomaly Detection
Diversity-Measurable Anomaly Detection
Wenrui Liu
Hong Chang
Bingpeng Ma
Shiguang Shan
Xilin Chen
23
56
0
09 Mar 2023
Normal Reference Attention and Defective Feature Perception Network for
  Surface Defect Detection
Normal Reference Attention and Defective Feature Perception Network for Surface Defect Detection
Wei Luo
Haiming Yao
Wenyong Yu
26
15
0
18 Nov 2022
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