Name
Title | ||
|---|---|---|
AF-RCNN: An anchor-free convolutional neural network for multi-categories agricultural pest detection. |
Abstract | ||
|---|---|---|
•An end-to-end two-stage framework is proposed for multi-classes agricultural pest detection.•A feature fusion module is introduced to enhance features representation of pest with small size.•We propose a new region proposal generation network without excessive hyper-parameters.•A matching algorithm based on the effective region of receptive field is used during training. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compag.2020.105522 | Computers and Electronics in Agriculture |
Keywords | DocType | Volume |
Agricultural pest detection,Fusion features,Anchor-free,RCNN,Region proposals | Journal | 174 |
ISSN | Citations | PageRank |
0168-1699 | 1 | 0.37 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Jiao | 1 | 3 | 2.44 |
| Shifeng Dong | 2 | 2 | 1.39 |
| Shengyu Zhang | 3 | 15 | 3.78 |
| Chengjun Xie | 4 | 51 | 9.17 |
| Hongqiang Wang | 5 | 1 | 0.37 |