An effective framework to detect the vehicle with improved accuracy using you only look once over Haar cascade

So that you may find out how well You Only Look Once works with OpenCV for speed-based car detection. This investigation involves two groups; one of them is the YOLO over OpenCV group. In each group, there are 10 participants, and the study settings for Glower are (α=0.05) and (power=0.85), both set...

Full description

Saved in:
Bibliographic Details
Main Authors: Babu, Harish, Velmurugan, J.
Format: Conference Proceeding
Language:English
Subjects:
Statistical methods
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:So that you may find out how well You Only Look Once works with OpenCV for speed-based car detection. This investigation involves two groups; one of them is the YOLO over OpenCV group. In each group, there are 10 participants, and the study settings for Glower are (α=0.05) and (power=0.85), both set simultaneously. When it comes to car detection, YOLO produces results that are 91% better than OpenCV’s 84% accuracy. The accuracy of the two methods differs by a statistically significant amount of p=0.639 when assessed with two tails. When it comes to identifying new Vehicle Detection, the SVM performs far better than the You Only Look Once model. One may argue that it’s the top choice for vehicle detection as well.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0228868