2010 Fiscal Year Final Research Report
Development of Multitask Pattern Recognition Model with Knowledge Transfer of Feature Space and Application to Person Identification
| Project/Area Number |
20500205
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Sensitivity informatics/Soft computing
|
|---|
| Research Institution | Kobe University |
|---|
Principal Investigator |
OZAWA Seiichi Kobe University, 大学院・工学研究科, 准教授 (70214129)
|
|---|
| Project Period (FY) |
2008 – 2010
|
| Keywords | ニューラルネット / マルチタスク学習 / 機械学習 / パターン認識 / 特徴抽出 |
|---|
| Research Abstract |
In the environments where multiple pattern recognition tasks with some relatedness are learned sequentially, it is known that the learning is conducted efficiently even with a small number of training data by using "knowledge transfer" from one task to another. In the research project, we developed a multitask learning algorithm with an efficient knowledge transfer mechanism where a useful feature space is learned incrementally in an efficient way by transferring a part of previous learned knowledge to an unknown task. The proposed multitask learning algorithm is implemented as a person identification system using face images and the effectiveness of this system is verified.
|
Research Products
(38 results)
