Tutorials, assignments, and competitions for MIT Deep Learning related courses.
-
Updated
Jan 3, 2024 - Jupyter Notebook
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.
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.
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
Convolutional Neural Network for German Traffic Sign Recognition Benchmark
Path planning implemented with behavior trees
Self-driving AI toy car 🤖🚗.
An Integrated Cyber-Physical Ecosystem for Autonomous Driving Research and Education
An Intelligent Modular Real-Time Vision-Based System for Environment Perception (NeurIPS 2022 Workshop)
My 10 takeaways from the 2019 Intelligent Vehicle Symposium
[IEEE RAL] Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications
Rich literature review and discussion on the implementation of "Hierarchical Decision-Making for Autonomous Driving"
Intelligent Driver Monitoring system for Autonomous Vehicles
Stereo depth estimation for self-driving cars 🚗
Semantic Understanding of Foggy Scenes with Purely Synthetic Data
Motion Control of Self-Driving Car for Trajectory Tracking
Add a description, image, and links to the self-driving-cars topic page so that developers can more easily learn about it.
To associate your repository with the self-driving-cars topic, visit your repo's landing page and select "manage topics."