| Project/Area Number |
24650119
|
|---|
| Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
Sensitivity informatics/Soft computing
|
|---|
| Research Institution | Kobe University |
|---|
Principal Investigator |
MATOBA OSAMU 神戸大学, システム情報学研究科, 教授 (20282593)
|
|---|
| Project Period (FY) |
2012-04-01 – 2014-03-31
|
| Project Status |
Completed (Fiscal Year 2013)
|
| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2013: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2012: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
|
|---|
| Keywords | 量子情報処理 / 物体認識 / 非構造化データ |
|---|
| Research Abstract |
In this research, we evaluated the effectiveness of the quantum object recognition algorithm to a large number of objects such as digital picture and digital movie that are unstructured and non-orthogonal data. In the developed quantum object recognition algorithm, quantum entanglement and quantum superposition are used to process the data with very high speed. To apply the developed algorithm to a large number of objects, a method of automatic feature extraction using SURF (Speeded Up Robust Features) and k-means is developed. As a large number of objects, 1,001 images such as alphabet are used. Four featured images to each original image are extracted. As a result, average probability amplitude of the detection of the correct image is 0.92. We confirmed that the developed algorithm has high recognition capability to a large number of objects.
|
