Unsupervised anomaly segmentation via deep feature reconstruction

f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks

(2019) Thomas Schlegl et al.   MEDICAL IMAGE ANALYSIS

Learning Deep Features for One-Class Classification

(2019) Pramuditha Perera et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Integrating prediction and reconstruction for anomaly detection

(2019) Yao Tang et al.   PATTERN RECOGNITION LETTERS

An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces

(2018) Shuang Mei et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

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

(2018) Paolo Napoletano et al.   SENSORS

Richer Convolutional Features for Edge Detection

(2018) Yun Liu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Defect Detection in SEM Images of Nanofibrous Materials

(2017) Diego Carrera et al.   IEEE Transactions on Industrial Informatics

Fully Convolutional Networks for Semantic Segmentation

(2017) Evan Shelhamer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION