研究実績の概要 |
This research aims to develop dynamic neural networks. Dynamic neural networks are neural networks that can adapt based on the input. A number of papers were successfully published. This includes three international conference papers, from ICASSP, ICPR, and ACMMM, and two Pattern Recognition journal papers. All of these papers are highly respected publications. There are a number of domestic publications as well.
Significant progress was done in dynamic temporal neural networks. Besides proposing novel models, new applications with real data were addressed. For example, a paper published at NLP 2023 used a new corpus that was created with a collaborator.
|