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Computer-Vision-based-Lane-Detection

Read this article: https://medium.com/@mihird97/lane-detection-an-instance-segmentation-based-approach-70f2de203886
Thanks to: Mihir Deshpande, Sreekar Lanka, Anushka Iyer, and Muskan Agarwal.

Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they “see.”

There are multiple applications in which machine learning and deep learning can be applied to images or videos to solve a real-world problem such as autonomous car driving.

Self-driving cars are autonomous decision-making systems. They can process streams of data from different sensors such as cameras, LiDAR, RADAR, GPS, or inertia sensors. This data is then modeled using deep learning algorithms, which then make decisions relevant to the environment the car is in.

LaneNet trained from Scratch

Lane Detection on Test Images

image

Reference

https://github.com/shirokunet/lane_segmentation

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