Table 2 Simplified names of datasets used and their description
From: Deep learning based deep-sea automatic image enhancement and animal species classification
Techniques | Short name | Description |
|---|---|---|
RAW | Dataset0 | Dataset with the original images |
DBY | Dataset1 | Dataset with the original images, but in colour (after the application of the debayering technique) |
DBY + WB | Dataset2 | Dataset containing images of the DBY dataset to which the White Balance (WB) method has been applied |
DBY + WB + GC | Dataset3 | Dataset containing images of the DBY + WB dataset to which the Gamma Correction (GC) method has been applied |
DBY + WB + GC + CLAHE | Dataset4 | Dataset containing images of the DBY + WB + GC dataset to which the CLAHE algorithm has been applied |
DBY + WB + ResidualCNN | Dataset5 | Dataset generated by the trained Residual CNN, using as input the colour images of the DBY dataset to which the WB method has been applied |
DBY + WB + GC + ResidualCNN | Dataset6 | Dataset generated by the trained Residual CNN, using as input the images of the DBY + WB + GC dataset |
DBY + WB + GC + CLAHE + ResidualCNN | Dataset7 | Dataset generated by the trained Residual CNN, using as input the images of the DBY + WB + GC + CLAHE dataset |