The project aims to detect lanes by applying different image processing techniques in Computer Vision which can be used in self-driving cars.
Lane detection is a critical component of self-driving cars and autonomous vehicles. Once lane positions are obtained, the vehicle will know where to go and avoid the risk of running into other lanes or getting off the road. This can prevent the driver/car system from drifting off the driving lane. There are multiple ways we can perform lane detection. We can use the learning-based approaches, such as training a deep learning model, However, there are simpler methods to perform lane detection as well. In this guided project, we will guide you in detecting lanes using Computer Vision with the popular OpenCV library in python.
Mentor Rating 4.8 / 5 (6)
American University of Sharja, Sharja,UAE
It was a fruitful experience. A clear road map was provided to follow throughout the project along with an in-depth introduction of the packages required. The guided labs were extremely helpful and easy to follow.
GITAM University,Hyderabad, India
The Guided Projects were not only based on solving real world problems but were also really informative, the smartinternz platform has each and every step in detail and even though if we were stuck at any point the Mentors would help us to resolve all our queries. overall it was a great experience.
College of Engineering and Technology, Bhubaneswar, Odisha, India
I took Part of Aritificial Intelligence Guided Project from Smartinternz, it was a wonderful experience and highly motivating, It's a very innovative and smart platform for internships. It provides smarter ways of guiding and interacting with participants and educating through guided labs and projects. It really helped me in giving a boost to my career.