| Pub. Date | : Feb' 2023 |
|---|---|
| Product Name | : The IUP Journal of Telecommunications |
| Product Type | : Article |
| Product Code | : IJTC040223 |
| Author Name | : Anand Dohare, Ajay Kumar Sahu, Swastika Sharma and Dushyant Bhati |
| Availability | : YES |
| Subject/Domain | : Arts & Humanities |
| Download Format | : PDF Format |
| No. of Pages | : 10 |
The development of intelligent motors heavily depends on lane detection. The paper proposes track detection to address issues like truncated detection accuracy of conventional techniques and poor real-time performance of sub-part of Machine Learning-based procedures. The proposed lane detection set of rules outperformed both traditional methods and Deep Learning-based methodologies in terms of accuracy, realtime performance, detection performance and interference resistance. Correct reputation cost and average processing time showed significant improvements. The provided set of guidelines is deemed to be essential for promoting the technological level of intelligent driver assistance and intelligent driver protection.
Robotic cars have been a dream for automobile companies worldwide, and many of them have tried to develop one. In the past few decades, with the advent of many technology companies, the market for cars has started to expand. The aim of this paper is to use Deep Learning techniques to create a method that enables the car to be driven in the proper direction on the roads.
CNN, Lane curvature, Track detection