Name
Abstract | ||
|---|---|---|
We propose a framework to detect lug position and orientation in robotics that is insensitive to the lug orientation, incorporating a proposed optimization based on the artificial bee colony genetic algorithm. Experimental results show that the proposed optimization method outperformed traditional artificial bee colony and other meta-heuristics in the considered cases and was up to 3 times faster than the traditional approach. The proposed detection framework provided excellent performance to detect lug objects for all test cases. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1587/transfun.E101.A.549 | IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES |
Keywords | Field | DocType |
artificial bee colony, object detection | Theoretical computer science,Artificial intelligence,Mathematics,Robotics | Journal |
Volume | Issue | ISSN |
E101A | 2 | 1745-1337 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Phuc Nguyen Hong | 1 | 15 | 2.20 |
| Jaehoon Jeong | 2 | 387 | 34.96 |
| Chang Wook Ahn | 3 | 759 | 60.88 |