| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
|
|---|
| Outline of Final Research Achievements |
Dictionary learning is a general name given to methods that features for decomposing observed data into a sparse linear combination. One achievement of this project was to develop a method of speeding up K-SVD, a widely-used method for dictionary learning, by
iterative projection onto lower dimensional subspace. The result was published as an article in the Journal of Information Processing by the Information Processing Society of Japan in May 2016. By applying the method to a set of images, an image feature database was constructed. In addition, a method of image classification using a Fisher kernel imposing sparsity was developed.
|
