Component-aware anomaly detection framework for adjustable and logical industrial visual inspection

This publication has 24 references indexed in Scilit:

• Reconstruction by inpainting for visual anomaly detection
  Pattern Recognition, 2021
• Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
• Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings
  2020
• Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection
  2019
• Invariant Information Clustering for Unsupervised Image Classification and Segmentation
  2019
• MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
  2019
• f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks
  Medical Image Analysis, 2019
• Computer-Vision-Based Fabric Defect Detection: A Survey
  IEEE Transactions on Industrial Electronics, 2008
• Image quality assessment: from error visibility to structural similarity
  IEEE Transactions on Image Processing, 2004
• A Threshold Selection Method from Gray-Level Histograms
  IEEE Transactions on Systems, Man, and Cybernetics, 1979