| Selective bit embedding scheme for robust blind color image watermarking T Huynh-The, CH Hua, NA Tu, T Hur, J Bang, D Kim, MB Amin, BH Kang, ... Information Sciences 426, 1-18, 2018 | 30 | 2018 |
| Encoding pose features to images with data augmentation for 3-D action recognition T Huynh-The, CH Hua, DS Kim IEEE Transactions on Industrial Informatics 16 (5), 3100-3111, 2019 | 19 | 2019 |
| MCNet: An efficient CNN architecture for robust automatic modulation classification T Huynh-The, CH Hua, QV Pham, DS Kim IEEE Communications Letters 24 (4), 811-815, 2020 | 15 | 2020 |
| Bimodal learning via trilogy of skip-connection deep networks for diabetic retinopathy risk progression identification CH Hua, T Huynh-The, K Kim, SY Yu, T Le-Tien, GH Park, J Bang, ... International journal of medical informatics 132, 103926, 2019 | 15 | 2019 |
| Hierarchical topic modeling with pose-transition feature for action recognition using 3D skeleton data T Huynh-The, CH Hua, NA Tu, T Hur, J Bang, D Kim, MB Amin, BH Kang, ... Information Sciences 444, 20-35, 2018 | 15 | 2018 |
| Image representation of pose-transition feature for 3D skeleton-based action recognition T Huynh-The, CH Hua, TT Ngo, DS Kim Information Sciences 513, 112-126, 2020 | 13 | 2020 |
| Convolutional networks with bracket-style decoder for semantic scene segmentation CH Hua, T Huynh-The, S Lee 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 13 | 2018 |
| Exploiting a low-cost CNN with skip connection for robust automatic modulation classification T Huynh-The, CH Hua, JW Kim, SH Kim, DS Kim 2020 IEEE Wireless Communications and Networking Conference (WCNC), 1-6, 2020 | 7 | 2020 |
| Learning action images using deep convolutional neural networks for 3d action recognition T Huynh-The, CH Hua, DS Kim 2019 IEEE Sensors Applications Symposium (SAS), 1-6, 2019 | 7 | 2019 |
| Cross-Attentional Bracket-shaped Convolutional Network for semantic image segmentation CH Hua, T Huynh-The, SH Bae, S Lee Information Sciences 539, 277-294, 2020 | 5 | 2020 |
| Learning 3D spatiotemporal gait feature by convolutional network for person identification T Huynh-The, CH Hua, NA Tu, DS Kim Neurocomputing 397, 192-202, 2020 | 5 | 2020 |
| Retinal vessel segmentation using round-wise features aggregation on bracket-shaped convolutional neural networks CH Hua, T Huynh-The, S Lee 2019 41st Annual International Conference of the IEEE Engineering in …, 2019 | 4 | 2019 |
| Locally statistical dual-mode background subtraction approach T Huynh-The, CH Hua, NA Tu, DS Kim IEEE Access 7, 9769-9782, 2019 | 4 | 2019 |
| Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images MA Al-antari, CH Hua, J Bang, S Lee Applied Intelligence, 1-18, 2020 | 3* | 2020 |
| ADM-HIPaR: An efficient background subtraction approach T Huynh-The, S Lee, CH Hua 2017 14th IEEE International Conference on Advanced Video and Signal Based …, 2017 | 3 | 2017 |
| Learning Constellation Map with Deep CNN for Accurate Modulation Recognition VS Doan, T Huynh-The, CH Hua, QV Pham, DS Kim arXiv preprint arXiv:2009.02026, 2020 | 2 | 2020 |
| Chain-Net: Learning Deep Model for Modulation Classification Under Synthetic Channel Impairment T Huynh-The, VS Doan, CH Hua, QV Pham, DS Kim arXiv preprint arXiv:2009.02023, 2020 | 2* | 2020 |
| Learning Geometric Features with Dual–stream CNN for 3D Action Recognition T Huynh-The, CH Hua, NA Tu, DS Kim ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 2* | 2020 |
| Physical Activity Recognition with Statistical-Deep Fusion Model using Multiple Sensory Data for Smart Health CH Hua, NA Tu, DS Kim IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021 | 1 | 2021 |
| Physical Activity Recognition with Statistical-Deep Fusion Model using Multiple Sensory Data for Smart Health T Huynh-The, CH Hua, NA Tu, DS Kim IEEE Internet of Things Journal, 2020 | 1 | 2020 |
Thien Huynh-TheKumoh National Institute of TechnologyVerified email at ieee.org
Thien Huynh-TheKumoh National Institute of TechnologyVerified email at ieee.org