Self-supervised representation learning anomaly detection methodology based on boosting algorithms enhanced by data augmentation using StyleGAN for manufacturing imbalanced data. - Yoonseok Kim; Taeheon Lee; Youngjoo Hyun; Eric Coatanéa; Siren Mika; Jeonghoon Mo; Youngjun Yoo (Comput. Ind., 2023)

Anomaly Detection via a Bottleneck Structure Robust to Noise in In-Distribution Samples. - Yeongkyu Cho; Donghwan Lee; Youngjoo Hyun; Wooju Kim (IEEE Access, 2024)

Extendable machine tool wear monitoring process using image segmentation based deep learning model and automatic detection of depth of cut line. - Youngjun Yoo; Gidong Yang; Kyunghee Park; Youngjoo Hyun; Seyun Jeong (Eng. Appl. Artif. Intell., 2024)