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Robert Grzelka's Projects

animal_detection_system icon animal_detection_system

This is my Thesis. In this project we implemented and studied an Animal Detection System, aiming at both high detection accuracy and computational efficiency. Specifically, we propose a two-stage detection method. The reason we employ two machine learning algorithms is the reduction of the false-positive rate and the execution time required for the multi-scale detection procedure of an input image. In the first stage, we use the Histogram of Oriented Gradient (HOG) [1] descriptor and a Support Vector Machine (SVM) [2] classifier that provides the next stage with a set of regions of interest (ROI) containing target animals and other false positive targets. Subsequently, the second stage, rejects the false positive ROIs by using a Convolutional Neural Network (CNN) [3] classifier. To train and evaluate the animal detector, we use CIFAR-10 dataset [7]. The purpose of this method was to detect animals from images and videos captured in natural scenes. For our experiments we used deers as the animal of choice.

applying_eanns icon applying_eanns

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.

apt-cyg icon apt-cyg

Apt-cyg, an apt-get like tool for Cygwin

arduinoradar icon arduinoradar

An Arduino and Python powered radar built using HF Ultrasonic sensors to map out surrounding obstacles onto a radar map using Python.

chinese-ufldl-tutorial icon chinese-ufldl-tutorial

[UNMAINTAINED] 非监督特征学习与深度学习中文教程,该版本翻译自新版 UFLDL Tutorial 。建议新人们去学习斯坦福的CS231n课程,该门课程在网易云课堂上也有一个配有中文字幕的版本。

cs231 icon cs231

My corrections for the Standford class assingments CS231n - Convolutional Neural Networks for Visual Recognition

cs231n-2017 icon cs231n-2017

Completed the CS231n 2017 spring assignments from Stanford university

cuda-convnet2 icon cuda-convnet2

Automatically exported from code.google.com/p/cuda-convnet2

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