Improvement in Deep Networks for Optimization Using eXplainable Artificial Intelligence. - Jin Ha Lee 002; Ik hee Shin; Sang gu Jeong; Seung-Ik Lee; Muhamamad Zaigham Zaheer; Beom-Su Seo (ICTC, 2019)

A Brief Survey on Contemporary Methods for Anomaly Detection in Videos. - Muhammad Zaigham Zaheer; Jin Ha Lee 002; Seung-Ik Lee; Beom-Su Seo (ICTC, 2019)

SmoothMix: a Simple Yet Effective Data Augmentation to Train Robust Classifiers. - Jin-Ha Lee 002; Muhammad Zaigham Zaheer; Marcella Astrid; Seung-Ik Lee (CVPR Workshops, 2020)

Old Is Gold: Redefining the Adversarially Learned One-Class Classifier Training Paradigm. - Muhammad Zaigham Zaheer; Jin-Ha Lee 002; Marcella Astrid; Seung-Ik Lee (CVPR, 2020)

For Safer Navigation: Pedestrian-View Intersection Classification. - Marcella Astrid; Jin Ha Lee 002; Muhammad Zaigham Zaheer; Jae-Yeong Lee; Seung-Ik Lee (ICTC, 2020)

Deep Visual Anomaly Detection with Negative Learning. - Jin Ha Lee 002; Marcella Astrid; Muhammad Zaigham Zaheer; Seung-Ik Lee (IW-FCV, 2021)

Cleaning Label Noise with Clusters for Minimally Supervised Anomaly Detection. - Muhammad Zaigham Zaheer; Jin-Ha Lee 002; Marcella Astrid; Arif Mahmood; Seung-Ik Lee (CoRR, 2021)

Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies. - Muhammad Zaigham Zaheer; Jin Ha Lee 002; Arif Mahmood; Marcella Astrid; Seung-Ik Lee (IEEE Trans. Image Process., 2022)