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autorc-neuralnets

A scaled down version of self-driving system using an RC car, Raspberry Pi, Arduino and open source software. The system uses a Raspberry Pi with a camera and an ultrasonic sensor as inputs, a processing computer that handles steering, object recognition (stop sign and traffic light) and distance measurement, and an Arduino board for RC car control.

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

behavioral_cloning

Deep learning to train an autonomous vehicle to mimic human driving

cnn-gtsrb

A simple CNN for the German Traffic Sign Recognition Benchmark(GTSRB).

co-training

Implementation of the Co-Training paper

comparing-trajectory-clustering-methods

Comparing Different Clustering Methods and Similarity Metrics on Trajectory Datasets

datasciencespecialization.github.io

http://DataScienceSpecialization.github.io

deep-learning-traffic-lights

Keras solution for recognizing traffic light from dash camera

deep-learning-traffic-lights-1

Code and files of the deep learning model used to win the Nexar Traffic Light Recognition challenge

deeplearningbook

MIT Deep Learning Book in PDF format

dissertate

Beautiful LaTeX dissertation templates.

educate-resource-for-machine-learning

This ebook from Jason Brownlee. Educational perpose only! Thanks to Jason for the books.

geonames-python

Python wrapper to Geonames webservice

gpsmachinelearning

gtsrb-caffe-model

German Traffic Sign Recognition Benchmark (GTSRB) AlexNet pycaffe model. http://benchmark.ini.rub.de/

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

isoxron

Creating isochrone maps for 1h, 2h, 3h, 4h

keras4gtsrb

Applying Deep Learning To Traffic Sign Recognition

lxmls-toolkit

Machine Learning applied to Natural Language Processing Toolkit used in the Lisbon Machine Learning Summer School

lxmls_guide

Lisbon Machine Learning Summer School Lab Guide

machine-learning-books

map_matching

Map Matching

mapillary_tools

Useful tools and scripts related to Mapillary

ml-traffic

Traffic sign recognition framework used for Kaggle competition

ml-traffic-sign-recognition

neuraltalk

NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.

neuraltalk2

Efficient Image Captioning code in Torch, runs on GPU

object-detection

Introduction The project presents an efficient method for object detection and demonstrates its use for real-time vision on-board vehicles. The work is closely based on Paul Viola’s face detection method [1], except that the system here was trained to detect objects related to traffic in order to assist the auto pilot on smart vehicles. The idea was adapted from D M Gavrila’s paper [2] REAL-TIME OBJECT DETECTION FOR "SMART" VEHICLES. Objective The target is to create Haar feature-based cascade classifiers by training the system with an appropriate amount of traffic related information in order to detect vehicles, pedestrians and traffic signs in real-time. Thus, this system in addition to driving assistance/collision avoidance, could further find its application in tracking and recognition.

object-detection-1

Introduction The project presents an efficient method for object detection and demonstrates its use for real-time vision on-board vehicles. The work is closely based on Paul Viola’s face detection method [1], except that the system here was trained to detect objects related to traffic in order to assist the auto pilot on smart vehicles. The idea was adapted from D M Gavrila’s paper [2] REAL-TIME OBJECT DETECTION FOR "SMART" VEHICLES. Objective The target is to create Haar feature-based cascade classifiers by training the system with an appropriate amount of traffic related information in order to detect vehicles, pedestrians and traffic signs in real-time. Thus, this system in addition to driving assistance/collision avoidance, could further find its application in tracking and recognition.