| Multiple feature integration for classification of thoracic disease in chest radiography TKK Ho, J Gwak Applied Sciences 9 (19), 4130, 2019 | 107 | 2019 |
| Self-supervised anomaly detection in computer vision and beyond: A survey and outlook H Hojjati, TKK Ho, N Armanfard Neural Networks, 106106, 2024 | 74 | 2024 |
| Utilizing knowledge distillation in deep learning for classification of chest X-ray abnormalities TKK Ho, J Gwak IEEE access 8, 160749-160761, 2020 | 67 | 2020 |
| Discrimination of mental workload levels from multi-channel fNIRS using deep leaning-based approaches TKK Ho, J Gwak, CM Park, JI Song IEEE Access 7, 24392-24403, 2019 | 64 | 2019 |
| Utilizing pretrained deep learning models for automated pulmonary tuberculosis detection using chest radiography TKK Ho, J Gwak, O Prakash, JI Song, CM Park Intelligent Information and Database Systems: 11th Asian Conference, ACIIDS …, 2019 | 57 | 2019 |
| Self-supervised learning for anomalous channel detection in EEG graphs: Application to seizure analysis TKK Ho, N Armanfard Proceedings of the AAAI conference on artificial intelligence 37 (7), 7866-7874, 2023 | 44 | 2023 |
| Deep leaning-based approach for mental workload discrimination from multi-channel fNIRS TKK Ho, J Gwak, CM Park, A Khare, JI Song Recent Trends in Communication, Computing, and Electronics: Select …, 2019 | 23 | 2019 |
| Deep learning-based multilevel classification of Alzheimer’s disease using non-invasive functional near-infrared spectroscopy TKK Ho, M Kim, Y Jeon, BC Kim, JG Kim, KH Lee, JI Song, J Gwak Frontiers in aging neuroscience 14, 810125, 2022 | 22 | 2022 |
| Graph Anomaly Detection in Time Series: A Survey TKK Ho, A Karami, N Armanfard arXiv preprint arXiv:2302.00058, 2023 | 18* | 2023 |
| Feature-level ensemble approach for COVID-19 detection using chest X-ray images TKK Ho, J Gwak Plos one 17 (7), e0268430, 2022 | 17 | 2022 |
| DeepADNet: A CNN‐LSTM model for the multi‐class classification of Alzheimer’s disease using multichannel EEG TKK Ho, YH Jeon, E Na, Z Ullah, BC Kim, KH Lee, JI Song, J Gwak Alzheimer's & Dementia 17, e057573, 2021 | 11 | 2021 |
| Toward deep learning approaches for learning structure motifs and classifying biological sequences from RNA A-to-I editing events TKK Ho, J Gwak IEEE Access 7, 127464-127474, 2019 | 5 | 2019 |
| Open-set multivariate time-series anomaly detection T Lai, TKK Ho, N Armanfard arXiv preprint arXiv:2310.12294, 2023 | 4 | 2023 |
| Multivariate time-series anomaly detection with contaminated data TKK Ho, N Armanfard arXiv preprint arXiv:2308.12563, 2023 | 4 | 2023 |
| Improving the multi‐class classification of Alzheimer’s disease with machine learning‐based techniques: An EEG‐fNIRS hybridization study TKK Ho, M Kim, YH Jeon, E Na, Z Ullah, BC Kim, KH Lee, JI Song, JG Kim, ... Alzheimer's & Dementia 17, e057565, 2021 | 3 | 2021 |
| Using artificial intelligence methods for dental image analysis: state-of-the-art reviews J Ahn, TKK Ho, J Kang, J Gwak Journal of Medical Imaging and Health Informatics 10 (11), 2532-2542, 2020 | 3 | 2020 |
| Noise Removal of Functional near Infrared Spectroscopy Signals Using Emperical Mode Decomposition and Independent Component Analysis PTK Chi, VN Tuan, NH Thuong, HTK Khanh, H Yu, ND Thang 6th International Conference on the Development of Biomedical Engineering in …, 2018 | 3 | 2018 |
| Graph-jigsaw conditioned diffusion model for skeleton-based video anomaly detection A Karami, TKK Ho, N Armanfard arXiv preprint arXiv:2403.12172, 2024 | 2 | 2024 |
| Machine learning–based detection model of early Alzheimer's disease using wearable device and gait assessment YH Jeon, TKK Ho, J Kang, BC Kim, KH Lee, JI Song, J Gwak Alzheimer's & Dementia 17, e057563, 2021 | 1 | 2021 |
| An EEG-fNIRS Hybridization Technique in the Multi-class Classification of Alzheimer's Disease Facilitated by Machine Learning TKK Ho, I Kim, Y Jeon, JI Song, J Gwak Proceedings of the Korean Society of Computer Information Conference, 305-307, 2021 | 1 | 2021 |