Table 9 Recall, precision, and F1-score of the multi-modal EfficientNetB7 + End-to-End CNN.
From: RGB-D based multi-modal deep learning for spacecraft and debris recognition
Category | Precision | Recall | F1-score |
|---|---|---|---|
AcrimSat | 0.87 | 0.96 | 0.91 |
Aquarius | 0.88 | 0.81 | 0.85 |
Aura | 0.94 | 0.93 | 0.94 |
Calipso | 0.79 | 0.78 | 0.78 |
Cloudsat | 0.83 | 0.33 | 0.48 |
CubeSat | 0.91 | 0.96 | 0.93 |
Debris | 0.81 | 0.96 | 0.87 |
Jason | 0.87 | 0.77 | 0.82 |
Sentinel-6 | 0.86 | 0.96 | 0.90 |
Terra | 0.77 | 0.82 | 0.79 |
TRMM | 0.85 | 0.92 | 0.88 |
Average | 0.85 | 0.84 | 0.83 |
