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 Intelligent Modular Real-Time Vision-Based System for Environment Perception (NeurIPS 2022 Workshop)
An Integrated Cyber-Physical Ecosystem for Autonomous Driving Research and Education
My 10 takeaways from the 2019 Intelligent Vehicle Symposium
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"
Stereo depth estimation for self-driving cars 🚗
Intelligent Driver Monitoring system for Autonomous Vehicles
Motion Control of Self-Driving Car for Trajectory Tracking
Semantic Understanding of Foggy Scenes with Purely Synthetic Data
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."