End-to-end Lane Detection for Self-Driving Cars (ICCV 2019 Workshop)
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Updated
May 14, 2020 - Python
End-to-end Lane Detection for Self-Driving Cars (ICCV 2019 Workshop)
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
Motion Planner for Self Driving Cars
Vehicle Detection with Convolutional Neural Network
Cooperative Driving Dataset: a dataset for multi-agent driving scenarios
Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications
Stereo depth estimation for self-driving cars 🚗
Intelligent Driver Monitoring system for Autonomous Vehicles
A macroscopic multivehicle tesbed and hardware-in-the-loop simulator for autonomous driving
Motion Control of Self-Driving Car for Trajectory Tracking
Using OpenCV to detect Lane Lines on a road, one of the most fundamental concepts for building a Self-Driving car.
We provide the code, pretrained models, and scripts to reproduce the experiments of the paper "Towards All-Weather Autonomous Driving". All code was implemented in Python using the deep learning framework PyTorch.
Behavioral Cloning Project for Self-Driving Car Nano Degree Term 1. The project includes designing a neural network and then training the car on the road in unity simulator. The CNN learns and clones the driving behavior.
A tool for predicting unsafe road scenarios for self-driving cars in BeamNG.tech.
To ease the driver to identify the Traffic Signs and also for the efficient working of Self-Driving Cars.
A practical implementation of pixel level segmentation based road detection and steering angle estimation methods.
Semantic Segmentation project for Autonomous Driving based on a TensorFlow implementation of UNet
A CNN built with Keras and trained to predict steering angles from camera input
Motion Planning and Control of Self-Driving Car
Autonomous RC Car using OpenCV,Python and Neural Network with Raspberry pi
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