ResNet-101 | Acc.(%) | Chalky | Non-chalky |
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Pre.(%) | Rec.(%) | F1(%) | Pre.(%) | Rec.(%) | F1(%) |
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Polished | 63.01 | 0.00 | 0.00 | 0.00 | 63.01 | 100.00 | 77.31 |
Unpolished | 83.43 | 98.50 | 82.19 | 89.61 | 43.65 | 91.67 | 59.14 |
Mixed | 84.20 | 98.08 | 83.45 | 90.18 | 44.77 | 89.17 | 59.61 |
- Three models are evaluated: 1) polished model trained on polished rice images; 2) unpolished model trained on Unpolished (12); 3) mixed model, obtained by further training the polished model using the Unpolished (12) images. Performance is reported in terms of Accuracy (Acc.), Precision (Pre.), Recall (Rec.) and F1 measure (F1). Precision, Recall and F1 measure values are reported separately for the Chalky and Non-Chalky classes. All three models are evaluated on the test subset corresponding to the Unpolished (12) rice images. The best performance for each type of model for each metric is highlighted using bold font