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RABEB FALEH HMIDI

Assistant Professor

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rfhmidi@ju.edu.sa
Computer Engineering & Networks - Computer and Information Sciences College
College
Computer and Information Sciences College
كلية علوم الحاسب والمعلومات
Department
Computer Engineering & Networks
هندسة الحاسب الألي والشبكات
Researches
2
2
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Current courses

Recent courses

Fm researches

Last Researches

A hybrid deep convolutional neural network-based electronic nose for pollution detection purposes
RABEB FALEH EP HMIDI
A new combined transient extraction method coupled with WO3 gas sensors for polluting gases classification
RABEB FALEH EP HMIDI

fm info

Researches

A hybrid deep convolutional neural network-based electronic nose for pollution detection purposes
RABEB FALEH EP HMIDI
A new combined transient extraction method coupled with WO3 gas sensors for polluting gases classification
RABEB FALEH EP HMIDI

Projects

Deep learning approaches based E-nose for pollution detection purposes
2024 - 2025

Because of their low cost, compact size, and fast response, electronic noses are widely employed in a
variety of industries, including medical care, food. The Electronic Nose (E-Nose) is a device that
simulates the human olfactory system. It assesses gases and scents qualitatively and quantitatively. It is
also referred to as a simulated olfactory system. It is made up of a sensor array, appropriate pre-processing
analysis, and a pattern recognition system for efficient classification. This research project proposes a

Wireless Electronic nose for environment safety purpose
2024 - 2025
Electronic Nose coupled with deep learning algorithms for early respiratory diseases diagnostics
2024 - 2025

Common respiratory tract infections can cause severe morbidity and mortality when they impact the lungs
and lower airways. Survival rates would be significantly higher if the disease was diagnosed and treated
clinically earlier. Many studies have shown that certain diseases and infections can result in characteristic
changes in VOC profiles in the exhaled breath. For the diagnosis of these conditions, a system and
apparatus that are simple to use, non-invasive, yield highly accurate results, and have the fewest possible

Education

M.A.
Sfax University - National School of Engineering
2011 - 2009
Ph.D.
Sfax University - National School of Engineering
2016 - 2012
BA
Sfax University - College of Sciences
2009 - 2005

Experience

Contracted Assistant
University of Monastir
2017 - 2018
Contracted Assistant professor
Sfax universuty
2016 - 2017
Contact