Table 4.

Comparison of our result with the state-of-the-art results on DFU classification.

Method	Recall (%)	Precision (%)	F-Score (%)
DFUNet [61]	92.5	93.8	93.1
DFU_QUTNet [59]	92.6	94.2	93.4
DFU_QUTNet + KNN [59]	92.7	93.8	93.2
DFU_QUTNet + SVM [59]	93.6	95.4	94.5
Ours (Phase #3)	99.81	98.7	99.25