. Author manuscript; available in PMC: 2023 Jan 31.

Published in final edited form as: Syst Sci Control Eng. 2022 Mar 6;10(1):325–335. doi: 10.1080/21642583.2022.2045645

Table 4. Performance comparison to State-of-the-art Approaches.

Method	Sen	Spc	Prc	Acc	F1	MCC	FMI
RBFNN [16]	66.89	75.47	73.23	71.18	69.88	42.56	69.97
RBFNN [16]	±2.43	±2.53	±1.48	±0.80	±1.08	±1.61	±1.04
WE-BBO [18]	72.97	74.93	74.48	73.95	73.66	47.99	73.66
WE-BBO [18]	±2.96	±2.39	±1.34	±0.98	±0.98	±2.00	±1.33
GLCM-SVM [17]	72.03	78.04	76.66	75.03	74.24	50.20	74.29
GLCM-SVM [17]	±2.94	±1.72	±1.07	±1.12	±1.57	±2.17	±1.53
WE-JAYA [19]	73.31	78.11	77.03	75.71	75.10	51.51	75.14
WE-JAYA [19]	±2.26	±1.92	±1.35	±1.04	±1.23	±2.07	±1.22
GoogLeNet [15]	77.64	83.85	82.82	80.74	80.12	61.65	80.17
GoogLeNet [15]	±2.22	±2.00	±1.54	±0.91	±1.07	±1.81	±1.05
WE-SAJ	85.47	87.23	87.03	86.35	86.23	72.75	86.24
WE-SAJ	±1.84	±1.67	±1.34	±0.70	±0.77	±1.38	±0.76

(Sen = Sensitivity; Spc = Specificity; Prc = Precision; Acc = Accuracy; F1 = F1 Score; MCC = Matthews correlation coefficient; FMI = Fowlkes-Mallows Index)