mohamedameen93 / Behavioral-Cloning-End-to-End-Learning-for-Self-Driving-Cars
In this project, I used a deep neural network (built with Keras) to clone car driving behavior. The dataset used to train the network is generated from Udacity's Self-Driving Car Simulator, and it consists of images taken from three different camera angles (Center - Left - Right), in addition to the steering angle, throttle, brake, and speed dur…
☆14Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for Behavioral-Cloning-End-to-End-Learning-for-Self-Driving-Cars
- Project on 3D Object Detection using Lyft's level5 dataset. Obtained mAP of 0.045 on the private leader board on kaggle and ranked in the…☆22Updated 4 years ago
- Computer Vision model to detect face in the first frame of a video and to continue tracking it in the rest of the video. This is implemen…☆29Updated 6 years ago
- The aim of this project is to allow a self driving car to steer autonomously in a virtual environment.☆22Updated 3 years ago
- StateFarm dataset used to predict the class of the distracted driver using VGG-16, RESNET50, XCEPTION and MOBILE NET models☆32Updated 4 years ago
- Saving incoming camera sensor images data as Numpy arrays to generate ground truth data for semantic segmentation☆26Updated 5 years ago
- Automatically classification of each driver's behavior given a dataset of 2D dashboard camera images.☆35Updated 6 years ago
- The system takes video footage of a highway as input and provides statistics like the count of vehicles and an average estimated speed of…☆60Updated 5 years ago
- YoLo is a CNN architecture which specialize in object detection. I am using tutorial from https://www.pyimagesearch.com/2018/11/12/yolo-o…☆18Updated 5 years ago
- ☆10Updated 4 years ago
- This project aims to detect the dangerous status of driving based on the images captured by the dashboard camera using deep learning.☆32Updated 7 years ago
- Trained MobilenetV2 model to recognize the distracted behaviors exhibited by drivers while driving. Deployed the Deep Learning model on t…☆14Updated 3 years ago
- Solves a kaggle problem of State Farm Distracted Driver Detection☆52Updated 3 months ago
- The "Driver Coach" system is based on a camera, sensors and machine learning algorithms. It monitors car driver behaviour and provides fe…☆25Updated 3 years ago
- This simulation of a car uses steering angle predictions from a convolutional neural network, this is also called end-to-end learning. It…☆21Updated 7 years ago
- ☆13Updated 3 years ago
- This is an implementation in Pytorch of nvidia's model to build a deep learning neural network for self-driving cars.☆22Updated 5 years ago
- Vehicle Detection + Advanced Lane Finding for ADAS☆35Updated 6 years ago
- Self Driving Cars Longitudinal and Lateral Control Design☆116Updated 5 years ago
- This repository contains code and writeups for projects and labs completed as a part of UDACITY's first of it's kind self driving car nan…☆49Updated last year
- Custom Object Detection With YoloV3☆18Updated 3 years ago
- Projects & Notebooks of Coursera's Self-Driving Cars Specialization.☆12Updated 2 years ago
- YOLO v3 Object Detection with Voice Feedback using gTTS☆48Updated 5 years ago
- Labeled Dataset for Object Detection in Carla Simulator☆44Updated last year
- Intelligent Driver Monitoring system for Autonomous Vehicles☆54Updated 4 years ago
- Udacity Self Driving Car Nanodegree - Vehicle Detection☆9Updated 6 years ago
- This project is my implementation of NVIDIA's PilotNet End to End deep CNN (built with Keras) to clone the behavior of a self driving c…☆9Updated 5 years ago
- Car crash detector from dashcam video using Convolutional neural network☆48Updated 4 years ago
- Hands-On Vision and Behavior for Self-Driving Cars, published by Packt☆56Updated last year
- My project and task solutions for Udacity's Self-driving Car Engineer Nanodegree☆32Updated last year