Name
Abstract | ||
|---|---|---|
In this paper, we study fingerprint feature extraction via CNN with Von Neumann neighborhood. The extraction was implemented by using CNN with nine input variables, and we find that the process could also be implemented with only five variables, and an easier algorithm without compromising the effectiveness. According to the CNN model with five input variables and the corresponding CNN gene bank done by Chen et al.[2006, Http1], we can determine the CNN gene easily. Simultaneously, we also find some results in one of the references are incorrect. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1142/S0218127407019676 | INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS |
Keywords | DocType | Volume |
fingerprint feature extraction, Cellular Neural Networks (CNN), Von Neumann, neighborhood, CNN gene bank | Journal | 17 |
Issue | ISSN | Citations |
11 | 0218-1274 | 2 |
PageRank | References | Authors |
0.51 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yijun Lou | 1 | 31 | 6.23 |
| Fang-yue Chen | 2 | 80 | 18.67 |
| Junbiao Guan | 3 | 34 | 7.69 |