{overleaf template gallery}LaTeX templates and examples — Recent

Unofficial beamer template for typesetting diploma thesis presentations - Department of Computer Engineering , Technological Educational Institute of Peloponnese, Greece. Based one the "beamer-greek-two" template provided by the Laboratory of Computational Mathematics, Mathematical Software and Digital Typography, Department of Mathematics, University of the Aegean. For an English version of this template see here.

The official masters and PhD thesis template for UNAL from the library. Retrieved 22 Oct 2014.

A sandbox to play with various useful packages, like qtree, shadedgauss, pfg-pie, bchart, dialogue, and booktabs. Contains citation commands for apacite bibliography style.

Codes TikZ des figures présents sur le cours "Les coniques" accessible à l'adresse : http://www.femto-physique.fr/mecanique/meca_complement2.php

Codes TikZ des figures du cours "Mouvememnts à force centrale" situé à l'adresse : http://www.femto-physique.fr/mecanique/meca_C7.php

Gesture recognition and its implementation that support Human Computer systems are becoming very popular mode of interaction now a days. It allows to interfacing the man machine commutative information flow naturally. Vision based gesture recognition has the potential that can provide intuitive and effective interaction between man and machine. However there are not adequate tools and techniques that support for developing, detecting or executing these tasks. In this paper we will implement a prototype that facilitates recording data during building some action based activities captured by the Kinect sensor. We analyze those recorded clips and visualize the user interactions by recognition the gestures objects based on depth, IR and skeletal data. Kinect tools include an analysis feature, a time-line-based approach that manually or automatically can mark the recording sequences of clips. We will implement both discrete and continuous gestures by using AdaBoast machine learning approach to detect hands activities. Our result suggest that the learning mechanism can achieve more than 98% of confidence level of given gestures. Keywords: Gesture recognition, Kinect, HCI, Machine learning, AdaBoost, Computer vision

Ce document regroupe les codes TIKZ des figures utilisées pour le cours "Les lentilles minces" situé à la page: http://femto-physique.fr/optique_geometrique/opt_C3.php

Beamer presentation template. For a modified version of this theme where the circular progress indicator goes a complete cycle and the logo and background image can be changed, use this template instead.

How to use biblatex with bibier and hyperref package.