Tongguang Ni
Biographic Data
| ID | 10055232 |
|---|---|
| NAME | Tongguang Ni |
| GIVEN NAMES | Tongguang |
| FAMILY NAME | Ni |
| SIGNATURE | NI T |
| AFFILIATIONS | Changzhou University |
| ORCID | 0000-0002-0354-5116 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Hierarchical Domain Adaptation Projective Dictionary Pair Learning Model for EEG Classification in IoMT Systems
Epilepsy recognition based on electroencephalogram (EEG) and artificial intelligence technology is the main tool of health analysis and diagnosis in Internet of medical things (IoMT). As a distributed learning framework, federated learning can train a shared model from multiple independent edge nodes using local data, which has greatly promoted the development of IoMT. One of the main challenges of EEG-based epilepsy recognition in IoMT is that E…
Transfer Model Collaborating Metric Learning and Dictionary Learning for Cross-Domain Facial Expression Recognition
Facial expression recognition has drawn increasing attention because of its great potential in human behavior analysis. Traditional recognition models usually assume that the training set is sufficient, and the training and testing data sets have the same distribution. However, these two factors are not satisfied in some cases. In this study, a transfer model collaborating metric learning and dictionary learning called TMMLDL is proposed to addre…
No prominent works on this page.
Transfer Model Collaborating Metric Learning and Dictionary Learning for Cross-Domain Facial Expression Recognition
Facial expression recognition has drawn increasing attention because of its great potential in human behavior analysis. Traditional recognition models usually assume that the training set is sufficient, and the training and testing data sets have the same distribution. However, these two factors are not satisfied in some cases. In this study, a transfer model collaborating metric learning and dictionary learning called TMMLDL is proposed to addre…
Hierarchical Domain Adaptation Projective Dictionary Pair Learning Model for EEG Classification in IoMT Systems
Epilepsy recognition based on electroencephalogram (EEG) and artificial intelligence technology is the main tool of health analysis and diagnosis in Internet of medical things (IoMT). As a distributed learning framework, federated learning can train a shared model from multiple independent edge nodes using local data, which has greatly promoted the development of IoMT. One of the main challenges of EEG-based epilepsy recognition in IoMT is that E…
Artificial Intelligence (2 works) · Computer Science (2 works) · Discriminative model (2 works) · Machine learning (2 works) · Machine Learning and ELM (2 works) · Speech recognition (2 works) · Advanced Memory and Neural Computing (1 works) · EEG and Brain-Computer Interfaces (1 works) · Electroencephalography (1 works) · Emotion and Mood Recognition (1 works)