Table 7 Recall, precision, and F1-score of the multi-modal ResNet50 + End-to-End CNN.
From: RGB-D based multi-modal deep learning for spacecraft and debris recognition
Category | Precision | Recall | F1-score |
|---|---|---|---|
AcrimSat | 0.81 | 0.92 | 0.86 |
Aquarius | 0.78 | 0.84 | 0.81 |
Aura | 0.90 | 0.87 | 0.88 |
Calipso | 0.78 | 0.76 | 0.77 |
Cloudsat | 0.77 | 0.34 | 0.48 |
CubeSat | 0.88 | 0.95 | 0.92 |
Debris | 0.72 | 0.90 | 0.80 |
Jason | 0.82 | 0.71 | 0.76 |
Sentinel-6 | 0.79 | 0.91 | 0.84 |
Terra | 0.75 | 0.67 | 0.70 |
TRMM | 0.86 | 0.80 | 0.83 |
Average | 0.81 | 0.79 | 0.79 |
