Approach | GT-known Loc. Acc. (%) | Loc. Acc. (%) | Avg. IoU (%) | Layer | T (%) |
|---|
Grad-CAM | 84.43 | 84.13 | 68.11 | layer2_0_conv2 | 60 |
Grad-CAM++ | 48.19 | 48.19 | 43.98 | layer2_0_conv2 | 60 |
Score-CAM | 68.07 | 66.87 | 55.02 | layer2_2_conv3 | 60 |
- Only 166 chalky seed images in the polished test set were used for chalkiness segmentation evaluation. Performance is reported using the following metrics: Ground-Truth Localization Accuracy (GT-known Loc. Acc.), which represents the fraction of ground-truth chalky seed images with \(\text{ IoU } \ge 0.5\); Localization Accuracy (Loc. Acc.), which represents the fraction of ground-truth chalky images, with \(\text{ IoU } \ge 0.5\), correctly predicted by the model; Average IoU (Avg. IoU), which represents the average IoU for the set of chalky seed images. To calculate the IoU, the mask of the predicted chalkiness is obtained using a threshold \(T=60\%\) of the maximum pixel intensity. The last two columns show the layer that was used for generating the heatmap and the threshold used to binarize the heatmap when calculating IoU, respectively
