NCTU DCP4121 Computer Science and Engineering Project I, II (Fall 2016, Spring 2017)

Hardware implementation for human detection by Histogram of Oriented Gradient (HOG)

Library for creating HoGs for use with machine learning etc.

Classifying CIFAR-10 dataset using simple classifiers

Face detection and recognition system implementation with HOG (Histogram of Oriented Gradients) based feature extraction.

Content-Based Image Retrieval System using multiple images deciphers for feature extraction

Histogram Of Oriented Gradients - C++

The repository is a part of an experiment, where a Stereo camera sensor was developed for Object detection and distance calculation using machine learning with HAAR-CASCADE- Classifier for an Autonomous Car. The idea was to compare the accuracy of a Stereo camera with that of LiDar sensors to cut down the overall cost of the system.

HOG feature descriptor, the kind of feature transform before we put our image into SVM. This repository also provides hog visualization both before and after doing block normalization.

Pedestrian detection with Python and OpenCV

A face recognition app using Python and OpenCV

Fast computation of rectangular histogram of oriented gradients (R-HOG) features using integral histogram

Detecting and Tracking Vehicles with Computer Vision + a Machine Learning Classifier

Códigos de Machine e Deep Learning

Edge driven, IoT based, intelligent system for restricted access control in commercial establishments. This project is a part of UNISYS Cloud 20/20 contest. Developed by students of BMSCE, Bengaluru

BRAN (Basic Recognition and Authentication at eNtrance) - A Facial recognition based identification & authentication system mounted at KI labs office entrance in Munich (https://www.ki-labs.com)