Table 4.

Comparative performance

Techniques	Classification accuracy (%)	Sensitivity	Specificity
FCM, shape, NN [50]	93.00	0.99	0.91
GLCM + SVM [27]	82.00	0.98	0.89
DWT + PCA [28]	95.00	0.99	0.88
HEDFD [29]	94.60	0.98	0.88
SVM + NN [49]	89.60	0.98	0.83
DNN [51]	96.00	1	0.98
ADR6-PCA*	90.15	0.98	0.87
ADR6-LDA*	97.93	1	0.93
ADR7-PCA*	95.26	0.96	0.93
ADR-7LDA*	97.28	1	0.99
SIFT-FV-PCA*	91.03	0.97	0.89
SIFT-FV-LDA*	94.40	0.94	0.93

* ADR states the proposed GMM-based AlexNet features