Computer-Aided Multiclass Classification of Corn from Corn Images Integrating Deep Feature Extraction

Table 3

Comparison of classification performances for all model.

Feature selection method	Number of selected attributes	Classifier	Performance
			ACC	TPR	TNR	PRE	F1-score	MCC
Deep feature extraction	1000	DT	70.59	66.73	90.54	66.77	66.74	57.24
		NB	72.15	68.35	91.05	68.71	68.40	59.52
		mSVM	89.40	87.63	96.62	87.63	87.63	84.24
		KNN	79.85	76.57	93.52	76.60	76.57	70.13
		NN	87.96	86.01	96.15	86.01	86.01	82.16
BA	480	DT	70.15	66.11	90.38	65.99	66.02	56.41
		NB	72.09	68.24	91.03	68.61	68.28	59.39
		mSVM	88.82	86.99	96.43	86.98	86.98	83.41
		KNN	79.87	76.58	93.53	76.65	76.57	70.16
		NN	87.38	85.32	95.96	85.32	85.32	81.28
WOA	315	DT	69.28	65.09	90.14	65.53	65.23	55.39
		NB	71.66	67.86	90.89	68.18	67.90	58.84
		mSVM	88.72	86.89	96.40	86.86	86.87	83.26
		KNN	79.61	76.31	93.45	76.33	76.31	69.79
		NN	87.26	85.16	95.92	85.20	85.18	81.10
GWO	384	DT	68.85	64.75	89.99	65.02	64.82	54.81
		NB	72.14	68.34	91.05	68.70	68.40	59.50
		mSVM	88.95	87.12	96.47	87.11	87.11	83.58
		KNN	80.12	76.84	93.61	76.91	76.85	70.51
		NN	87.30	85.20	95.93	85.23	85.21	81.15