Sep.2018 - May.2022
- Improve physiological emotion recognition by 3.5% UAR using Transformer-based User-Centered modeling.
- Improve physiological personality recognition by 8% UAR through Auditorial-Visual guided Graphical Attention Networks.
Sep.2016 - May.2022
- Propose a Privacy-aware learning strategy FedCM improving heterogeneity Federated Learning on Medical Images.
- Brought neuroscientific insights into the brain’s functional connectivity and the mechanism of face processing and memory.
Jan.2021 - Dec.2021
- Propose a Mixed-Domain Self-Attention Resnet (MDARsn) using Reduced-Lead ECG for Heart Disease Detection.
- Winner of the Best Challenge Poster in PhysioNet/CinC Challenge 2021.
Sep.2018 - May.2022
- Study on Acoustic/Linguistic and Physiological signals fusion algorithms for group dynamics modeling.
- Design a Multi-modality Multi-subjects group interaction dataset.
Jan 2020 - Dec 2021
- Develop real-time deep CRNN AI de-reverberation engine with SRMR 4.774.
- Lead development of speech cloning from unseen sources using Generative Adversarial Networks.
Mar 2020 - Nov 2020
- Lead the development of deep video retrieval system speeding up the fake news screening using Pytorch and Ranking algorithm.
- Build the system with Flask and Docker with Retrieval Precision 95.1%.
- The system would be deployed by two NGO fake news checkersTaiwan FactCheck Center and MyGoPen.
Jan 2018 - Jan 2019
- Shopping conversion prediction based on user website traversal graph.
- Customer pattern recognition for automatically clustering user groups for precise marketing.
Sep 2016 - Sep 2018
- Develop deep Speech/Face/Gesture Multi-modal behavior profiling system for AI hiring recommendation.
- Construct a Multi-person Multi-modal real-time data collection system.
1. Hao-Chun Yang and Chi-Chun Lee, “A Media-Guided Attentive Graphical Network for Personality Recognition Using Physiology” IEEE Transactions on Affective Computing (IF 10.5)
1. Ya-Lin Huang, Hao-Chun Yang, and Chi-Chun Lee, “Federated Learning via Conditioned Mutual Learning for Alzheimer Disease Classification on T1w MRI” 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, (Virtual), Nov 1-5, 2021
2. Hao-Chun Yang, Wan-Ting Hsieh, and Pei-Chun Chen, “A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram” Computing in Cardiology, CinC 2020, Brno, Czech Republic, September 12-15
3. Woan-Shiuan Chien, Hao-Chun Yang, and Chi-Chun Lee, “Cross Corpus Physiological-based Emotion Recognition Using a Learnable Visual Semantic Graph Convolutional Network” MM ’20: The 28th ACM International Conference on Multimedia, ACMMM 2020, Virtual Event / Seattle, WA, USA, October 12-16, 2020
4. Hao-Chun Yang and Chi-Chun Lee, “A Siamese Content-Attentive Graph Convolutional Network for Personality Recognition Using Physiology” 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020
Sep.2018 - May.2022
- Improve physiological emotion recognition by 3.5% UAR using Transformer-based User-Centered modeling.
- Improve physiological personality recognition by 8% UAR through Auditorial-Visual guided Graphical Attention Networks.
Sep.2016 - May.2022
- Propose a Privacy-aware learning strategy FedCM improving heterogeneity Federated Learning on Medical Images.
- Brought neuroscientific insights into the brain’s functional connectivity and the mechanism of face processing and memory.
Jan.2021 - Dec.2021
- Propose a Mixed-Domain Self-Attention Resnet (MDARsn) using Reduced-Lead ECG for Heart Disease Detection.
- Winner of the Best Challenge Poster in PhysioNet/CinC Challenge 2021.
Sep.2018 - May.2022
- Study on Acoustic/Linguistic and Physiological signals fusion algorithms for group dynamics modeling.
- Design a Multi-modality Multi-subjects group interaction dataset.
Jan 2020 - Dec 2021
- Develop real-time deep CRNN AI de-reverberation engine with SRMR 4.774.
- Lead development of speech cloning from unseen sources using Generative Adversarial Networks.
Mar 2020 - Nov 2020
- Lead the development of deep video retrieval system speeding up the fake news screening using Pytorch and Ranking algorithm.
- Build the system with Flask and Docker with Retrieval Precision 95.1%.
- The system would be deployed by two NGO fake news checkersTaiwan FactCheck Center and MyGoPen.
Jan 2018 - Jan 2019
- Shopping conversion prediction based on user website traversal graph.
- Customer pattern recognition for automatically clustering user groups for precise marketing.
Sep 2016 - Sep 2018
- Develop deep Speech/Face/Gesture Multi-modal behavior profiling system for AI hiring recommendation.
- Construct a Multi-person Multi-modal real-time data collection system.
1. Hao-Chun Yang and Chi-Chun Lee, “A Media-Guided Attentive Graphical Network for Personality Recognition Using Physiology” IEEE Transactions on Affective Computing (IF 10.5)
1. Ya-Lin Huang, Hao-Chun Yang, and Chi-Chun Lee, “Federated Learning via Conditioned Mutual Learning for Alzheimer Disease Classification on T1w MRI” 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, (Virtual), Nov 1-5, 2021
2. Hao-Chun Yang, Wan-Ting Hsieh, and Pei-Chun Chen, “A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram” Computing in Cardiology, CinC 2020, Brno, Czech Republic, September 12-15
3. Woan-Shiuan Chien, Hao-Chun Yang, and Chi-Chun Lee, “Cross Corpus Physiological-based Emotion Recognition Using a Learnable Visual Semantic Graph Convolutional Network” MM ’20: The 28th ACM International Conference on Multimedia, ACMMM 2020, Virtual Event / Seattle, WA, USA, October 12-16, 2020
4. Hao-Chun Yang and Chi-Chun Lee, “A Siamese Content-Attentive Graph Convolutional Network for Personality Recognition Using Physiology” 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020