Grad-CAM (ResNet-101) | GT-known Loc. Acc. (%) | Loc. Acc. (%) | Avg. IoU (%) | Layer | T (%) |
|---|
polished model | 7.92 = 019/240 | 7.92 = 19/240 | 26.79 | layer2_0_ conv2 | 60 |
unpolished model | 63.75 = 153/240 | 63.75 = 153/240 | 51.76 | layer2_0_ conv2 | 60 |
mixed model | 20.42 = 049/240 | 20.42 = 049/240 | 29.91 | layer2_3_ conv2 | 60 |
- Only 240 chalky seed images in the Unpolished (12) 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
