Name
Abstract | ||
|---|---|---|
In this paper, the authors propose an adaptive Elastic Net method for edge linking of images. Edge linking is a fundamental computer-vision task, which is a constrained optimization problem. In the proposed method, an adaptive dynamic parameter strategy and a stochastic noise strategy are introduced into the Elastic Net, which enables the network to have superior ability for escaping from local minima and converge sooner to optimal or near-optimal solutions. Simulations confirm that the proposed method could produce more meaningful contours than the original Elastic Net in shorter time. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.4018/IJITN.2015040101 | IJITN |
Keywords | DocType | Volume |
Adaptive Computer Vision, Edge Linking, Elastic Net | Journal | 7 |
Issue | ISSN | Citations |
2 | 1941-8663 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junyan Yi | 1 | 0 | 0.34 |
| Gang Yang | 2 | 32 | 9.38 |
| Xiaoxuan Ma | 3 | 0 | 0.68 |
| Xiaoyun Shen | 4 | 0 | 0.34 |