| Project/Area Number |
25871033
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Intelligent informatics
Perceptual information processing
|
|---|
| Research Institution | National Institute of Technology, Toyama College |
|---|
Principal Investigator |
KITAMURA Takuya 富山高等専門学校, 電気制御システム工学科, 助教 (40611918)
|
|---|
| Project Period (FY) |
2013-04-01 – 2015-03-31
|
| Project Status |
Completed (Fiscal Year 2014)
|
| Budget Amount *help |
¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2014: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
|
|---|
| Keywords | パターン認識 / 機械学習 / サポートベクトルマシン / スパース / オンライン学習 |
|---|
| Outline of Final Research Achievements |
In this research, I have developed sparse support vector machine for big problem which sequentially-add categories. For example, I apply this system to face identification which sequentially-add the categories (registrants). Then, this problem may be too big. However, this system uses only a new added category in training when this category is added. Using face identification problem and multi-category benchmark datasets, I evaluate the effectiveness of this system.
|
