Neural Batch Sampling with Reinforcement Learning for Semi-supervised Anomaly Detection

Deep Residual Learning for Image Recognition

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Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

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MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection

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A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

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Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks

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Automatic Road Crack Detection Using Random Structured Forests

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Adversarially Learned One-Class Classifier for Novelty Detection

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Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images

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Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

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Robust PCA via Outlier PursuitPreprint

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Training Adversarial Discriminators for Cross-Channel Abnormal Event Detection in Crowds

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Defect Detection in SEM Images of Nanofibrous Materials

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Coherence Pursuit: Fast, Simple, and Robust Principal Component Analysis

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Pavement Distress Detection Using Random Decision Forests

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Real-time texture error detection on textured surfaces with compressed sensing

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Generalized Out-of-Distribution Detection: A Survey

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Deep Industrial Image Anomaly Detection: A Survey

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Deep reinforcement learning in computer vision: a comprehensive survey

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Deep Learning for Unsupervised Anomaly Localization in Industrial Images: A Survey

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IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing

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Glancing at the Patch: Anomaly Localization with Global and Local Feature Comparison

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Federated Anomaly Analytics for Local Model Poisoning Attack

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Survey on industrial defect detection with deep learning

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Intelligent Model Update Strategy for Sequential Recommendation

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Computer Vision – ECCV 2020

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Unsupervised Anomaly Detection on Attributed Networks With Graph Contrastive Learning for Consumer Electronics Security

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The survey of industrial anomaly detection for industry 5.0

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Double Deep Q-Network Next-Generation Cyber-Physical Systems: A Reinforcement Learning-Enabled Anomaly Detection Framework for Next-Generation Cyber-Physical Systems

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An Uncertainty Quantification and Calibration Framework for RUL Prediction and Accuracy Improvement

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Anomaly detection via gating highway connection for retinal fundus images

Zhang, W., Liu, H., Xie, J., Huang, Y., Zhang, Y., Li, Y., Ramachandra, R., & Zheng, Y. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.110167 · Cited by 14 · see citing works

A Novel MAE-Based Self-Supervised Anomaly Detection and Localization Method

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Semi-supervised noise-resilient anomaly detection with feature autoencoder

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Outlier Detection with Reinforcement Learning for Costly to Verify Data

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MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement LearningPreprint

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Unsupervised Industrial Anomaly Detection Based on Feature Mask Generation and Reverse Distillation

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Frequency domain nuances guided parallel transformer model for industrial anomaly localization

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Defect Detection in High-Speed Railway Overhead Contact System: Importance, Challenges, and Methods

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Advancements in AI-Based Anomaly Detection for Smart Manufacturing

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Comparison of unsupervised image anomaly detection models for sheet metal glue lines

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AM-CFDN: semi-supervised anomaly measure-based coal flow foreign object detection network

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A survey of historical learning: learning models with learning history

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Anomaly Detection of Integrated Circuits Package Substrates Using the Large Vision Model SAIC: Dataset Construction, Methodology, and Application

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Contrastive Knowledge Distillation for Anomaly Detection in Multi-Illumination/Focus Display Images

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Efficient industrial point cloud anomaly detection via spatial context aggregation and selective anomalous feature generation

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Mtddpm: A Novel Visual Anomaly Detection Method Based on Multiscale Denoising Diffusion Probabilistic ModelPreprint

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Enhancing Anomalous Sound Detection with Multi-Level Memory Bank

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Deep Embedded Auto-encoder for End-to-End Unsupervised Image Anomaly Detection

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A Semi-supervised Reinforcement Learning Framework Incorporating the Multi-scale IncepMambaNet Network for Glaucoma Progression Prediction

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Anomaly Synthesis Strategy With Gabor Convolutional Kernel and Vision Transformer

Ha, M.-H., & Park, T.-H. (2025) · IEEE Access · doi:10.1109/access.2025.3613732

Minimal discriminative learning for open set recognition

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DRL-Guided Neural Batch Sampling for Semi-Supervised Pixel-Level Anomaly Detection

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Reconstruction error-based anomaly detection with few outlying examples

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Semi-Supervised Learning for Defect Segmentation with Autoencoder Auxiliary Module

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GANomaly: Semi-supervised Anomaly Detection via Adversarial Training

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Semi-supervised Anomaly Detection Using GANs for Visual Inspection in Noisy Training Data.Preprint

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