Table 1 Experimental results on the NEU-MGD multi-objects data set.
From: Robot multi-target high performance grasping detection based on random sub-path fusion
Network name | ACC (%) | LOSS | Fps |
|---|---|---|---|
RSPFG-Net | 96.39 | 0.0175 | 45 |
SqueezeNet | 74.32 | 0.025 | 14 |
Faster-RCNN | 85.6 | 0.035 | 11 |
CascadeR-CNN | 91.5 | 0.024 | 22 |
GG-CNN | 73 | 0.0272 | 19 |
AlexNet | 88 | 0.026 | 13 |
FCGN | 97.7 | 0.0226 | 9 |
ResNet-50x2 | 89.2 | 0.0275 | 10 |
