Name
Abstract | ||
|---|---|---|
Character recognition collects item keywords from images from e-commerce websites; however, it requires a huge amount of training data. In this paper, we propose an efficient method to collect the training data by generating synthesis images and emphasizing outlines to obtain realistic images. The proposed method improves recognition accuracy on both generated images and real images from e-commerce websites. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-66715-7_70 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Character recognition,Synthesis image,CNN | Training set,Pattern recognition,Character recognition,Computer science,Word recognition,Artificial intelligence,Real image | Conference |
Volume | ISSN | Citations |
10507 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yukihiro Achiha | 1 | 0 | 0.34 |
| Takayoshi Yamashita | 2 | 377 | 46.83 |
| Mitsuru Nakazawa | 3 | 4 | 3.92 |
| Soh Masuko | 4 | 54 | 15.69 |
| Yuji Yamauchi | 5 | 43 | 10.45 |
| fujiyoshi | 6 | 730 | 101.43 |