Name
Abstract | ||
|---|---|---|
•Proposing a pigeon behavior detection method base on YOLO v4 deep learning algorithm.•Using self-made data sets, comparison of multiple target detection models and comparison of multiple lightweight feature extraction networks.•Comparative study between parameter, weight size, computation, accuracy and FPS.•The proposed method contributes to the development of dovecote inspection robots. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.compag.2022.107032 | Computers and Electronics in Agriculture |
Keywords | DocType | Volume |
Target detection,Pigeon cleaning behavior,Light-weight network,YOLO v4,Ghostnet | Journal | 199 |
ISSN | Citations | PageRank |
0168-1699 | 0 | 0.34 |
References | Authors | |
0 | 12 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianjun Guo | 1 | 0 | 0.68 |
| Guohuang He | 2 | 0 | 0.34 |
| Hao Deng | 3 | 0 | 0.34 |
| Wenting Fan | 4 | 0 | 0.34 |
| Longqin Xu | 5 | 0 | 1.01 |
| Liang Cao | 6 | 0 | 0.34 |
| Dachun Feng | 7 | 0 | 0.34 |
| Jingbin Li | 8 | 0 | 1.01 |
| Huilin Wu | 9 | 0 | 0.34 |
| Jiawei Lv | 10 | 0 | 0.34 |
| Shuangyin Liu | 11 | 0 | 1.01 |
| Shahbaz Gul Hassan | 12 | 0 | 0.68 |