Profile Norhene GARGOURI
First Name
Norhene
Last Name
GARGOURI
Address
Technopole of Sfax, PO Box 275, Sakiet Ezzit, 3021 Sfax - Tunisia
Zip code
3038
Biography
Dr. Norhène Gargouri Ben Ayed is an Associate Professor at the Digital Research Center of Sfax in Tunisia. She is a member of the SM@RT Laboratory and contributes to the Computers Imaging and Electronics Systems (CIELS) research team. Her research focuses on medical image processing, where she integrates advanced techniques such as deep learning, machine learning, and artificial neural networks.
Dr. Gargouri has authored over 25 scientific publications, with more than 260 citations. Her notable contributions include breast cancer anomaly detection using possibility theory and clustering paradigms, as well as the development of automatic breast computer-aided diagnosis (CAD) systems based on weighted feature fusion and deep convolutional neural networks.
In addition to her research activities, she serves as the President of the Association for Scientific Research (ABORS), reflecting her dedication to scientific advancement and collaboration.
Dr. Gargouri holds a Professional Doctorate in Engineering (PDEng) from the National Engineering School of Sfax, where she specialized in electrical engineering. She has also earned her University Habilitation, qualifying her to supervise doctoral research.
Research Interests
IA, Medical image processing
Scientific publications
| Title | Cited by | Year |
|---|---|---|
Artificial Intelligence in Pulmonary ImagingNorhene Gargouri, Nesrine Charfi, Malek Laadhar, Wiem FekiIntroduction to the Opportunities, Risks, and Future Directions of AI in …, 2027 |
0 | 2027 |
DI-EffNet: A Dual-Attention Network for Binary ILD Classification from Imbalanced CT Data.N Gargouri, N Charfi, AD Masmoudi, W Feki, C DamakInternational Journal of Online & Biomedical Engineering 22 (1), 2026 |
0 | 2026 |
Towards Robust and Clinically Reliable Lung CT Segmentation Using Deeply Supervised U-Net++N Gargouri, N Lamred, N Charfi, A Damak, W Feki2025 IEEE 22nd International Conference on Sciences and Techniques of …, 2025 |
0 | 2025 |
Breast cancer anomaly detection based on the possibility theory with a clustering paradigmJF Elleuch, MZ Mehdi, M Belaaj, NG Benayed, D Sellami, A DamakBiomedical Signal Processing and Control 79, 104043, 2023 |
12 | 2023 |
Entropy-based traffic flow labeling for CNN-based traffic congestion prediction from meta-parametersMZ Mehdi, HM Kammoun, NG Benayed, D Sellami, AD MasmoudiIEEE Access 10, 16123-16133, 2022 |
64 | 2022 |
