Convolutional Neural Network Based Vehicle Classification in Adverse Illuminous Conditions for Intelligent Transportation Systems

Table 6

Comparison of the proposed method with existing state-of-the-art vehicle classification methods.

Method(s)	Accuracy (in percentage)						Total
	Bus	Car	Motorbike	Rickshaw	Truck	Van
Zhuo et al. [44]	95.76	94.70	96.67	95.11	95.45	92.25	95.49
Gao et al. [45]	91.78	95.28	97.03	98.77	93.35	91.43	92.61
Shivai et al. [46]	88.17	90.42	91.78	83.37	89.71	89.11	88.96
Zakria et al. [11]	90.55	91.26	97.73	93.36	94.76	88.99	92.77
Proposed method	99.48	99.68	99.08	100.0	100.0	99.65	99.68