Prof. Ridha Ejbali | Multimedia System | Best Researcher Award
Prof. Ridha Ejbali, Research Team in Intelligent Machines, Tunisia
Prof. Ridha Ejbali, a distinguished academic from Tunisia š¹š³, is renowned for his expertise in the field of Information Systems. With a Research Habilitation and Doctorate from the National Engineering School of Sfax (ENIS), University of Sfax, Tunisia š, Prof. Ejbali has held key positions at the Faculty of Sciences of Gabes (FSG), University of Gabes, Tunisia, serving as both Associate Professor and Assistant Professor š«. His dedication to academia extends to his roles as a member of the Scientific Council, Head of IT Department, and President of the UTT club “Teck Unified Team” at FSG. Prof. Ejbali’s research focuses on intelligent machines, encompassing areas such as machine learning, deep learning, pattern recognition, computer vision, classification, and security, as part of the Research Team in Intelligent Machines (RTIM) at FSG.
š Professional Profile:
š Qualifications
- Research Habilitation in Engineering of Information Systems (July 2018): National Engineering School of Sfax (ENIS), University of Sfax, Tunisia
- Doctorate in Engineering of Information Systems (December 2012): National Engineering School of Sfax (ENIS), University of Sfax, Tunisia
š« Professional Experience
- Associate Professor (2020 ā Present): Faculty of Sciences of Gabes (FSG), University of Gabes, Tunisia
- Assistant Professor (2014 ā 2020): Faculty of Sciences of Gabes (FSG), University of Gabes, Tunisia
š Responsibilities & Pedagogical Activities
- Member of the Scientific Council at the Faculty of Sciences of Gabes since January 2021
- Head of IT Department at the Faculty of Sciences of Gabes (September 2017 – January 2021)
- President of UTT club “Teck Unified Team” at the Faculty of Sciences of Gabes since 2015
š§ Research Work & Affiliations
- Affiliation: Research Team in Intelligent (RTIM) at the Faculty of Sciences of Gabes
- Research Topics: Machine learning, deep learning, pattern recognition, computer vision, classification, security
Publication Top Notes:
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Stacked sparse autoencoder and history of binary motion image for human activity recognition
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Journal: Multimedia Tools and Applications
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Citations: 58
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A distributed coverage hole recovery approach based on reinforcement learning for Wireless Sensor Networks
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Journal: Ad Hoc Networks
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Citations: 56
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Deep wavelet network for image classification
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Conference: 2016 IEEE International conference on systems, man, and cybernetics
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Citations: 49
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Wavelet network for recognition system of Arabic word
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Journal: International Journal of Speech Technology
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Citations: 43
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A hybrid approach for content-based image retrieval based on fast beta wavelet network and fuzzy decision support system
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Journal: Machine Vision and Applications
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Citations: 41
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