Jongmin Yu

Orcid: 0000-0001-9996-734X

According to our database1, Jongmin Yu authored at least 45 papers between 2014 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Weakly Supervised Contrastive Learning for Unsupervised Vehicle Reidentification.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination.
IEEE Trans. Neural Networks Learn. Syst., October, 2024

Road Surface Defect Detection - From Image-Based to Non-Image-Based: A Survey.
IEEE Trans. Intell. Transp. Syst., September, 2024

Breaking Down Financial News Impact: A Novel AI Approach with Geometric Hypergraphs.
CoRR, 2024

Multi-class Road Defect Detection and Segmentation using Spatial and Channel-wise Attention for Autonomous Road Repairing.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
Active anomaly detection based on deep one-class classification.
Pattern Recognit. Lett., March, 2023

Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection.
CoRR, 2023

Multi-source Domain Adaptation for Unsupervised Road Defect Segmentation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
Abnormal Event Detection and Localization via Adversarial Event Prediction.
IEEE Trans. Neural Networks Learn. Syst., 2022

Unusual Insider Behavior Detection Framework on Enterprise Resource Planning Systems Using Adversarial Recurrent Autoencoder.
IEEE Trans. Ind. Informatics, 2022

Abnormal event detection using adversarial predictive coding for motion and appearance.
Inf. Sci., 2022

Graph-structure based multi-label prediction and classification for unsupervised person re-identification.
Appl. Intell., 2022

Predictively encoded graph convolutional network for noise-robust skeleton-based action recognition.
Appl. Intell., 2022

Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

A federated binarized neural network model for constrained devices in IoT healthcare services.
Proceedings of the 2022 International Conference on Artificial Intelligence in Information and Communication, 2022

2021
Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination.
CoRR, 2021

Unsupervised Person Re-identification via Multi-Label Prediction and Classification based on Graph-Structural Insight.
CoRR, 2021

Real-Time Abnormal Insider Event Detection on Enterprise Resource Planning Systems via Predictive Auto-Regression Model.
IEEE Access, 2021

Unsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020
Action matching network: open-set action recognition using spatio-temporal representation matching.
Vis. Comput., 2020

Carbon price interaction between allocated permits and generated offsets.
Oper. Res., 2020

Boosting Network Weight Separability via Feed-Backward Reconstruction.
IEEE Access, 2020

Unsupervised Pixel-level Road Defect Detection via Adversarial Image-to-Frequency Transform.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

Context-Aware Multi-Task Learning for Traffic Scene Recognition in Autonomous Vehicles.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

2019
Driver Drowsiness Detection Using Condition-Adaptive Representation Learning Framework.
IEEE Trans. Intell. Transp. Syst., 2019

Drivers Drowsiness Detection using Condition-Adaptive Representation Learning Framework.
CoRR, 2019

Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning.
CoRR, 2019

Boosting Network Weight Separability via Feed-Backward Reconstruction.
CoRR, 2019

Spatio-Temporal Representation Matching-Based Open-Set Action Recognition by Joint Learning of Motion and Appearance.
IEEE Access, 2019

Unconstrained Face Verification and Open-World Person Re-identification via Densely-connected Convolution Neural Network.
Proceedings of the 14th International Joint Conference on Computer Vision, 2019

RTS Smoother for GLMB filter.
Proceedings of the 2019 International Conference on Control, 2019

Spatio-Temporal Feature Extraction and Distance Metric Learning for Unconstrained Action Recognition.
Proceedings of the 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2019

2018
Joint representation learning of appearance and motion for abnormal event detection.
Mach. Vis. Appl., 2018

Deep Discriminative Representation Learning for Face Verification and Person Re-Identification on Unconstrained Condition.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

Parasitic Network: Learning-Based Network Downsizing of Very Deep Neural Networks for Computer Vision.
Proceedings of the 2018 International Conference on Control, 2018

2017
Automatic part localization using 3D cuboid box for vehicle subcategory recognition.
Proceedings of the International Conference on Control, 2017

Learning Feature Representation for Face Verification.
Proceedings of the 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2017

2016
Abnormal Event Detection using Scene Partitioning by Regional Activity Pattern Analysis.
Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016), 2016

Gaussian-Poisson mixture model for anomaly detection of crowd behaviour.
Proceedings of the 2016 International Conference on Control, 2016

Feature flow-based abnormal event detection using a scene-adaptive cuboid determination method.
Proceedings of the 2016 International Conference on Control, 2016

Representation Learning, Scene Understanding, and Feature Fusion for Drowsiness Detection.
Proceedings of the Computer Vision - ACCV 2016 Workshops, 2016

2015
An incremental learning approach for restricted boltzmann machines.
Proceedings of the 2015 International Conference on Control, 2015

2014
Background subtraction based on Gaussian mixture models using color and depth information.
Proceedings of the International Conference on Control, 2014

Heart Beat Detection Method with Estimation of Regular Intervals between ECG and Blood Pressure.
Proceedings of the Computing in Cardiology, CinC 2014, 2014


  Loading...