Tutorials, assignments, and competitions for MIT Deep Learning related courses.
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Updated
Jan 3, 2024 - Jupyter Notebook
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.
DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.
End-to-end Lane Detection for Self-Driving Cars (ICCV 2019 Workshop)
Vehicle Detection with Convolutional Neural Network
Motion Planner for Self Driving Cars
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
Convolutional Neural Network for German Traffic Sign Recognition Benchmark
Path planning implemented with behavior trees
Lane Finding Project for Self-Driving Car ND
Intelligent Driver Monitoring system for Autonomous Vehicles
An Intelligent Modular Real-Time Vision-Based System for Environment Perception (NeurIPS 2022 Workshop)
Self-Driving Cars with ROS 2 and Autoware
Cooperative Driving Dataset: a dataset for multi-agent driving scenarios
Using OpenCV to detect Lane Lines on a road, one of the most fundamental concepts for building a Self-Driving car.
Attacking Vision based Perception in End-to-end Autonomous Driving Models
Stereo depth estimation for self-driving cars 🚗
Rich literature review and discussion on the implementation of "Hierarchical Decision-Making for Autonomous Driving"
Self-driving AI toy car 🤖🚗.
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