machine learning

Finding optimal number of Clusters by using Cluster validation

This module finds the optimal number of components (number of clusters) for a given dataset. In order to find the optimal number of components for, first we used k-means algorithm with a different number of clusters, starting from 1 to a fixed max number. Then we checked the cluster validity by deploying \( C-index \) algorithm and …

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Car Detection Using Single Shot MultiBox Detector (SSD Convolutional Neural Network) in ROS Using Caffe

This work is similar to the previous work here, but this time I used Single Shot MultiBox Detector (SSD) for car detection. Installation is similar, clone the  SSD Caffe:

add the following lines to your Makefile.config

and build it:

used video_stream_opencv to stream your video:

download the trained model from here and put them in the model …

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Car Detection Using Fast Region-based Convolutional Networks (R-CNN) in ROS with Caffe

To run this, you need to install Fast-RCNN and Autoware. Just in case you got error regarding hd5f when making Fast-RCNN, add the following lines to your Makefile.config

Now run the following command to start:

if you got an error like :

That means your graphics card is not ready or accessible, in my everytime I suspend my notebook I get that …

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Octomap explanierend

In this tutorial, I explain the concept, probabilistic sensor fusion model and the sensor model used in Octomap library. related publication: OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees 1)Octamap Volumetric Model 2)Probabilistic Sensor Fusion Model 3)Sensor Model for Laser Range Data    

Gaussian Mixture Regression

Gaussian Mixture Regression is basically Multivariate normal distribution with Conditional distribution. The more about the theory could be found at  [1], [2], [3], [4]. For this work, I have added the functionality of adding Gaussian Mixture Regression to this project on the GitHub by forking the main project, my forked project can be download at here Github The main changes …

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Expectation Maximization algorithm to obtain Gaussian mixture models for ROS

I found a really good code at GitHub for fitting a Gaussian Mixture Model (GMM) with Expectation Maximization (EM) for ROS. There are so many parameters that you can change. Some of the most important ones are:

To find the optimal number of components, it uses Bayesian information criterion (BIC). There are other methods to find …

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Multi scale face detector using HOG features and support vector machine

In this part, I trained an SVM over images of  “face” or “not face” (36 × 36 pixels), using HOG features. I used VLFeat library for both HOG and the SVM. Example of face images: Example of nonface images: I divided the dataset into a training and a test set (80% and 20% respectively) and computed the HOG …

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2D pose estimation of human body using CNS and PCA

This work is the second part of my master thesis (part I). In this part, I developed an algorithm for 2D pose estimation of the human body. To do this, I created a software with QT that could generate 2D contours representing human body. Then I send these contours for evaluation to CNS(Contrast Normalized Sobel) [1] …

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Human detection on mobile camera using HOG and tracking them using Kalman filter

This is the part I of the work that I did for my master thesis (part II). In this work first, I computed HOG (Histogram of oriented gradients) on my images and then sent the computed histogram to a linear SVM (support vector machine). The SVM was trained with human and non-human images. The output of the classifier was …

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