Moving Vehicle Detection and Classification Using Gaussian Mixture Model and Ensemble Deep Learning Technique

Table 2

Performance analysis of the proposed ensemble deep learning technique on the BIT Vehicle Dataset in terms of precision, recall, and accuracy.

Feature extraction	Classifier	Precision (%)	Recall (%)	Accuracy (%)
SPT	MSVM	64.90	78	75
	KNN	69	60.83	72
	DNN	70.45	72	62.43
	LSTM	73.97	80.80	79.60
	Ensemble	78.91	86.82	90
WLD	MSVM	70	75	80
	KNN	70.02	79.97	81
	DNN	78.20	86.55	81.02
	LSTM	79	84.60	83.20
	Ensemble	81.02	84.39	86.22
Hybrid (SPT + WLD)	MSVM	82.94	92.19	93
	KNN	87	92	94.94
	DNN	92.28	97.20	96.66
	LSTM	93.90	96.97	98.98
	Ensemble	98.24	99.72	99.28