Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.

Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream

Computer Vision and Image Recognition algorithms for R users

Convolutional Autoencoder for Loop Closure

Training SVM classifier to recognize people expressions (emotions) on Fer2013 dataset

Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.

HOG feature extractor with simple python implementation

A vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM).

Detects Pedestrians in images using HOG as a feature extractor and SVM for classification

This repository contains works on a computer vision software pipeline built on top of Python to identify Lanes and vehicles in a video. This project is not part of Udacity SDCND but is based on other free courses and challanges provided by Udacity. It uses Computer vision and Deep Learrning Techniques. Few pipelines have been tried on SeDriCa, I…

Detecting Cars in real time and identifying the speed of cars and tracking

Image processing Toolkit in R

SVM using HOG descriptors implemented in fragment shaders

MATLAB implementation of a basic HOG + SVM pedestrian detector.

Android application which uses feature extraction algorithms and machine learning (SVM) to recognise and translate static sign language gestures.

Histogram Of Oriented Gradients

Detecting Cars in real time and identifying the speed of cars and tracking

Face detection implementation with different methods and applications

Python module for face recognition with OpenCV and Deep Learning.

Term 1, Project 5 - Udacity Self Driving Car Nanodegree