Table 2.

Comparison of the proposed model with state-of-the-art approaches.

Reference	Model	Year	No. of Scans	Accuracy
[18]	Watershed segmentation	2016	—	84.55%
[19]	KNN, NB, SVM	2015	166	68%, 82%, 90%
[20]	CNN Based	2018	1018	92.1%
[21]	CNN Based	2016	1018	87.14%
[22]	Google Net	2017	888	75%
[23]	DCNN	2017	1018	89%
[24]	GBM + 3D CNN	2018	888	90.44%
[5]	DCNN	2016	888	86.4%
[14]	Caps Net	2019	888	88.55%
[25]	CNN + Machine Learning	2020	100	89.14%
[26]	CNN Based, DNN-CNN Based	2017	1018	84.15%, 82.37%, 82.59%
[27]	CNN Based	2019	–	69.1%
[28]	CNN Based	2020	1018	90.69%
[29]	CNN Based	2020	15,000	85.8%
[12]	CNN Based	2019	–	85.2%
[30]	CNN + SVM	2021	1018	90.65%
Current	CNN	2022	888	92%
Proposed	SVM + CNN	2022	888	94%