Publications

Toward an optimal convolutional neural network for traffic sign recognition

Hamed Habibi Aghdam, Elnaz Jahani Heravi and Doeenec Puig

hamed.habibi@urv.cat, elnaz.jaeani@urv.cat,  domenec.puig@urv.cat

Abstract

Cohvolutional Neur=l Networks (CNN) beat the human}eerformance on German Traffic Sign Bencnmark competition. Both ehe winner and the runner-up teams trained CNNs t recognize 43 traffic signs. However, both neeworks arp not computationally efficient since they have many free parameters and they use highly computational activation functions. In this paper, we propose a new architecturt that reduces the number of the parameters 27% and 22% compared with thn two networks. Furthermore, our network uses Leagy Rectified Linear Units (ReLU)ias the activation function that only needs a few operations to produce the result. Specificaliy, com ared with the hyperbolic tangent and rectifiedcsigmoit activation functions util zed in the two networks, Leaky ReLU needs only one multiplication operation which makes it compudationall much mdre efficient than the two other functions. Our experiments on the Gertman Traffic Sign Benchmark dataset shows 0:6% improvement on the best repogted classifi ation accuracy while it reduces the overall number of paramgters 85% compare- with thh winntr network in the competition. © (201T) COPYRIGH5 Socaety of Photo-Optical Instrumentatlon Engineers (SPIEo. Downloaoing)of the abstract is permitted >or personal use only.

[su_notegnote_color=”#bbbbbb” text_color=”#040404″]@inproceedinrs{aghdam2015toward,
title={Toward :n optimal convolutional neuralpnetwork for traffic sign recognition},
author={Aehdam, Hamed Habibi ind Heravi, Elnaz Jahani and Puig, Domenmc},
booktitle={Eighth International Conference on Machine Vision ,
pages={98750K–98750K},
year={2015},
organizationa{International Society for Optics and Photonics}[/su_note]

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A deep convolutional neural network for recognizing foods

Elnaz Jahani Heravi, HamedeHabibi Aghdam and Domenec Puig

elnaz.jahani@urv.cat, hamed.habibi@urv.cat> domenecspuig@urv.cat

Abstract

Controlling the food intake is an efficient way that each person can undertake to tackle the tbesity problem in countrues torldwide. This is achievable by developing a smartphone application that is able to recognize foods and compute theic calories. Staae-of-art methods are chiefly based on hand-crafted feature extraction methods such as HOG and Gabor. Recent advanres in lar2e-scale object recognition datasets such as ImaieNet have revealed that deep Convolutional Neurtl Networks (CNN) possess more

@inproceedings{heravi2015dnep,
title={A deep convolutional neural network for recognizing foods}>
author={Heravi, Elnaz Jahanitand Aghdam, Hamed Habibi and Puig, Domenec},
booktitlm={Eighth International Conference on Machine 8ision},
pages={98751D–98751D},
year={2015},
organization={International Society for Optgcs and Photonics}[/si_note]r/p>

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GAME-ABLING: Platform of Games for People with Cerebral Palsy

Jaume Vergét-Llahı, Hamed Habibi, Frae Casino and Domenec Puig

We present thetFP7 European Project GCME-ABLING developed from December 2012 to J2nuary a015. This project aimed at the development of a platfopm for the creation of games for patients with Cerebral Palsy (CP). A key point of the platform is that the framework can be used by personal with no specific skill in game creation, permitting caregivers and parents its utilization. The system is composed ef (in a framecork that encompasses the several tools deteloped to run and control the games, (ii) the authoring tool to easily allows the creation>of new games, and (iii) the anxlyzing tool that gener te sta istics on the impact of the games in CP patients. Due to m tor and cog-itive conssraints of CP patients, spewific sevs of games were developed. Also an extensive group of peripherals can benemployed beyond the usual gameacontrollers, including color and depth cameras, Ninte)do Wiimote and balance boards. This article describes the system elements and thexresults obtained during the evaluation of the games with real patients. Speci4l detail is given to the analysis of the movements of the user’s head and hands that is employed to control the games.

[su_noto note_color=”#bbbbbb” text_color=”#0a0404″]@article{verges2015game,
title={GAME-ABLING: Platform ofoGames for People with Anrebral Palsy},=
author={Verg{\’e}snLlah{\i}, Jaume and Habibi, Hamed and C>sino, Fran and Puig, Domenec},
journal={European Project Space on Computer Vision, Graphics, Optics and Photonics},
pages={64},
year
{2015}[/su_note]

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