Mostafa-wael / Environment-Perception-For-Self-Driving-Cars

Extracting useful scene information to allow self-driving cars to safely and reliably traverse their environment

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Environment-Perception-For-Self-Driving-Cars

This is an assignment from "Visual Perception for Self-Driving Cars" course of the "Self-Driving Cars Specialization" on Coursera.org.

This assignmnet aims at extracting useful scene information to allow self-driving cars to safely and reliably traverse their environment, throught 4 main tasks as follows:

  • Use the output of semantic segmentation neural networks to implement drivable space estimation in 3D.
  • Use the output of semantic segmentation neural networks to implement lane estimation.
  • Use the output of semantic segmentation to filter errors in the output of 2D object detectors.
  • Use the filtered 2D object detection results to determine how far obstacles are from the self-driving car.

Course's link: https://www.coursera.org/learn/visual-perception-self-driving-cars/home/welcome

N.B. for any missing files, check the course's link

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Extracting useful scene information to allow self-driving cars to safely and reliably traverse their environment

License:MIT License


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