Heart Beat Detection Method with Estimation of Regular Intervals between ECG and Blood Pressure. - Jongmin Yu; Taegyun Jeon; Moongu Jeon (CinC, 2014)

Background subtraction based on Gaussian mixture models using color and depth information. - Young-Min Song; SeungJong Noh; Jongmin Yu; Cheonwi Park; Byung-Geun Lee (ICCAIS, 2014)

An incremental learning approach for restricted boltzmann machines. - Jongmin Yu; Jeonghwan Gwak; Sejeong Lee; Moongu Jeon (ICCAIS, 2015)

Representation Learning, Scene Understanding, and Feature Fusion for Drowsiness Detection. - Jongmin Yu; Sangwoo Park; Sangwook Lee; Moongu Jeon (ACCV Workshops (3), 2016)

Feature flow-based abnormal event detection using a scene-adaptive cuboid determination method. - Hae-Rim Shin; Jeonghwan Gwak; Jongmin Yu; Moongu Jeon (ICCAIS, 2016)

Gaussian-Poisson mixture model for anomaly detection of crowd behaviour. - Jongmin Yu; Jeonghwan Gwak; Moongu Jeon (ICCAIS, 2016)

Abnormal Event Detection using Scene Partitioning by Regional Activity Pattern Analysis. - Jongmin Yu; Jeonghwan Gwak; SeongJong Noh; Moongu Jeon (VISIGRAPP (3: VISAPP), 2016)

Learning Feature Representation for Face Verification. - Sangwoo Park; Jongmin Yu; Moongu Jeon (AVSS, 2017)

Automatic part localization using 3D cuboid box for vehicle subcategory recognition. - Younkwan Lee; Jongmin Yu; Moongu Jeon (ICCAIS, 2017)

Parasitic Network: Learning-Based Network Downsizing of Very Deep Neural Networks for Computer Vision. - Jongmin Yu; Duyoung Kim; Moongu Jeon (ICCAIS, 2018)

Deep Discriminative Representation Learning for Face Verification and Person Re-Identification on Unconstrained Condition. - Jongmin Yu; Donghwuy Ko; Hangyul Moon; Moongu Jeon (ICIP, 2018)

Joint representation learning of appearance and motion for abnormal event detection. - Jongmin Yu; Kin Choong Yow 001; Moongu Jeon (Mach. Vis. Appl., 2018)

Spatio-Temporal Feature Extraction and Distance Metric Learning for Unconstrained Action Recognition. - Yongsang Yoon; Jongmin Yu; Moongu Jeon (AVSS, 2019)

RTS Smoother for GLMB filter. - Tran Thien Dat Nguyen; Jongmin Yu (ICCAIS, 2019)

Unconstrained Face Verification and Open-World Person Re-identification via Densely-connected Convolution Neural Network. - Donghwuy Ko; Jongmin Yu; Ahmad Muqeem Sheri; Moongu Jeon (VISIGRAPP (5: VISAPP), 2019)

Spatio-Temporal Representation Matching-Based Open-Set Action Recognition by Joint Learning of Motion and Appearance. - Yongsang Yoon; Jongmin Yu; Moongu Jeon (IEEE Access, 2019)

Boosting Network Weight Separability via Feed-Backward Reconstruction. - Jongmin Yu; Younkwan Lee; Moongu Jeon (CoRR, 2019)

Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning. - Jongmin Yu (CoRR, 2019)

Drivers Drowsiness Detection using Condition-Adaptive Representation Learning Framework. - Jongmin Yu; Sangwoo Park; Sangwook Lee; Moongu Jeon (CoRR, 2019)

Driver Drowsiness Detection Using Condition-Adaptive Representation Learning Framework. - Jongmin Yu; Sangwoo Park; Sangwook Lee; Moongu Jeon (IEEE Trans. Intell. Transp. Syst., 2019)

Context-Aware Multi-Task Learning for Traffic Scene Recognition in Autonomous Vehicles. - Younkwan Lee; Jihyo Jeon; Jongmin Yu; Moongu Jeon (IV, 2020)

Unsupervised Pixel-level Road Defect Detection via Adversarial Image-to-Frequency Transform. - Jongmin Yu; Du Yong Kim; Younkwan Lee; Moongu Jeon (IV, 2020)

Boosting Network Weight Separability via Feed-Backward Reconstruction. - Jongmin Yu; Hyeontaek Oh (IEEE Access, 2020)

Carbon price interaction between allocated permits and generated offsets. - Jongmin Yu; Mindy L. Mallory (Oper. Res., 2020)

Action matching network: open-set action recognition using spatio-temporal representation matching. - Jongmin Yu; Du Yong Kim; Yongsang Yoon; Moongu Jeon (Vis. Comput., 2020)

Unsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary. - Jongmin Yu; Hyeontaek Oh (IROS, 2021)

Real-Time Abnormal Insider Event Detection on Enterprise Resource Planning Systems via Predictive Auto-Regression Model. - Jongmin Yu; Minkyung Kim 001; Hyeontaek Oh; Jinhong Yang (IEEE Access, 2021)

Unsupervised Person Re-identification via Multi-Label Prediction and Classification based on Graph-Structural Insight. - Jongmin Yu; Hyeontaek Oh (CoRR, 2021)

Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination. - Jongmin Yu; Hyeontaek Oh; Minkyung Kim 001; Junsik Kim 001 (CoRR, 2021)

A federated binarized neural network model for constrained devices in IoT healthcare services. - Hyeontaek Oh; Jongmin Yu; Nakyoung Kim; Dongyeong Kim; Jangwon Lee; Jinhong Yang (ICAIIC, 2022)

Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics. - Minkyung Kim 001; Junsik Kim 001; Jongmin Yu; Jun Kyun Choi (ICDM (Workshops), 2022)

Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification. - Jongmin Yu; Junsik Kim 001; Minkyung Kim 001; Hyeontaek Oh (ICRA, 2022)

Predictively encoded graph convolutional network for noise-robust skeleton-based action recognition. - Yongsang Yoon; Jongmin Yu; Moongu Jeon (Appl. Intell., 2022)

Graph-structure based multi-label prediction and classification for unsupervised person re-identification. - Jongmin Yu; Hyeontaek Oh (Appl. Intell., 2022)

Abnormal event detection using adversarial predictive coding for motion and appearance. - Jongmin Yu; Jung-Gyun Kim; Jeonghwan Gwak; Byung-Geun Lee; Moongu Jeon (Inf. Sci., 2022)

Unusual Insider Behavior Detection Framework on Enterprise Resource Planning Systems Using Adversarial Recurrent Autoencoder. - Jongmin Yu; Hyeontaek Oh; Minkyung Kim 001; Sehun Jung (IEEE Trans. Ind. Informatics, 2022)

Abnormal Event Detection and Localization via Adversarial Event Prediction. - Jongmin Yu; Younkwan Lee; Kin Choong Yow 001; Moongu Jeon; Witold Pedrycz (IEEE Trans. Neural Networks Learn. Syst., 2022)

Multi-source Domain Adaptation for Unsupervised Road Defect Segmentation. - Jongmin Yu; Hyeontaek Oh; Sebastiano Fichera; Paolo Paoletti; Shan Luo 001 (ICRA, 2023)

Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection. - Jongmin Yu; Hyeontaek Oh; Jinhong Yang (CoRR, 2023)

Active anomaly detection based on deep one-class classification. - Minkyung Kim 001; Junsik Kim 001; Jongmin Yu; Jun Kyun Choi (Pattern Recognit. Lett., 2023)

Multi-class Road Defect Detection and Segmentation using Spatial and Channel-wise Attention for Autonomous Road Repairing. - Jongmin Yu; Chen Bene Chi; Sebastiano Fichera; Paolo Paoletti; Devansh Mehta; Shan Luo 001 (ICRA, 2024)

Breaking Down Financial News Impact: A Novel AI Approach with Geometric Hypergraphs. - Anoushka Harit; Zhongtian Sun; Jongmin Yu; Noura Al Moubayed (NLP4KGC@SEMANTiCS, 2024)

Adversarial Diffusion Model for Unsupervised Domain-Adaptive Semantic Segmentation. - Jongmin Yu; Zhongtian Sun; Shan Luo 001 (CoRR, 2024)

Denoising diffusion model with adversarial learning for unsupervised anomaly detection on brain MRI images. - Jongmin Yu; Hyeontaek Oh; Younkwan Lee; Jinhong Yang (Pattern Recognit. Lett., 2024)

Road Surface Defect Detection - From Image-Based to Non-Image-Based: A Survey. - Jongmin Yu; Jiaqi Jiang; Sebastiano Fichera; Paolo Paoletti; Lisa Layzell; Devansh Mehta; Shan Luo 001 (IEEE Trans. Intell. Transp. Syst., 2024)

An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination. - Minkyung Kim 001; Jongmin Yu; Junsik Kim 001; Tae-Hyun Oh; Jun Kyun Choi (IEEE Trans. Neural Networks Learn. Syst., 2024)

Weakly Supervised Contrastive Learning for Unsupervised Vehicle Reidentification. - Jongmin Yu; Hyeontaek Oh; Minkyung Kim 001; Junsik Kim 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Adversarially Domain-adaptive Latent Diffusion for Unsupervised Semantic Segmentation. - Jongmin Yu; Zhongtian Sun; Chen Bene Chi; Jinhong Yang; Shan Luo 001 (CVPR Workshops, 2025)

Advanced Hypergraph Mining for Web Applications Using Sphere Neural Networks. - Zhongtian Sun; Anoushka Harit; Jongmin Yu; Jingyun Wang; Pietro Liò (WWW (Companion Volume), 2025)