A
Ahmed Ben Hamida
Researcher at University of Sfax
Publications - 177
Citations - 1194
Ahmed Ben Hamida is an academic researcher from University of Sfax. The author has contributed to research in topics: Computer science & Fault detection and isolation. The author has an hindex of 16, co-authored 156 publications receiving 902 citations. Previous affiliations of Ahmed Ben Hamida include Texas A&M University & École Normale Supérieure.
Papers
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A New Adaptive Gamma Correction Based Algorithm Using DWT-SVD for Non-Contrast CT Image Enhancement
Fathi Kallel,Ahmed Ben Hamida +1 more
TL;DR: An advanced adaptive and simple algorithm for dark medical image enhancement based on adaptive gamma correction using discrete wavelet transform with singular-value decomposition (DWT-SVD-AGC) is proposed and shows that it performs better than other state-of-the-art techniques.
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3D multimodal MRI brain glioma tumor and edema segmentation: A graph cut distribution matching approach
Ines Njeh,Lamia Sallemi,Ismail Ben Ayed,Khalil Chtourou,Stéphane Lehéricy,Damien Galanaud,Ahmed Ben Hamida +6 more
TL;DR: This study investigates a fast distribution-matching, data-driven algorithm for 3D multimodal MRI brain glioma tumor and edema segmentation in different modalities, which yields a highly competitive performance for complete edema and tumor segmentation, among nine existing competing methods.
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Statistical Fault Detection of Chemical Process - Comparative Studies
Majdi Mansouri,Mohammed Zs,Raoudha Baklouti,Mohamed Nounou,Hazem Nounou,Ahmed Ben Hamida,Nazmul Karim +6 more
TL;DR: The objective of this work is to improve the PCA-based fault detection by using more sophisticated FD charts to achieve further improvements and widen the applicability of the process monitoring techniques in practice.
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Monitoring of wastewater treatment plants using improved univariate statistical technique
TL;DR: This paper is to develop univariate statistical technique that aims at enhancing the monitoring of wastewater treatment plants using an improved particle filtering (IPF)-based multiscale optimized exponentially weighted moving average chart (MS-OEWMA).
Journal Article
An Optimal Unsupervised Satellite image Segmentation Approach Based on Pearson System and k-Means Clustering Algorithm Initialization
TL;DR: This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization and it exploited Pearson system for an optimal statistical distributions' affectation of each considered class.