Meziane Iftene | Artificial Neural Networks | Research Excellence Award

Dr. Meziane Iftene | Artificial Neural Networks | Research Excellence Award

Agence Spatiale Algérienne | Algeria

Dr. Meziane Iftene is a researcher at the Algerian Space Agency specializing in remote sensing, deep learning, and geospatial data fusion. He has authored and co-authored overpeer-reviewed publications in leading international conferences and journals. His work focuses on hyperspectral unmixing, very high-resolution image classification, and AI-driven environmental monitoring, including forest mapping and precision agriculture. He has led R&D initiatives, supervised nanosatellite projects, and contributed to national space system development such as the Alsat-3 program. Through international collaborations, his research advances GeoAI solutions for sustainable environmental management and intelligent Earth observation systems.

Citation Metrics (Scopus)

40

30

20

10

0

Citations
23

Documents
15

h-index
3

🟦 Citations 🟥 Documents 🟩 h-index

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Featured Publications


Very high resolution images classification by fusing deep convolutional neural networks.

– In Proceedings of the 5th International Conference on Advanced Computer Science and Technology (ACSAT 2017). (2017). Cited By: 6

Transfering super resolution convolutional neural network for remote sensing data sharpening.

In Proceedings of the 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2018). (2018). Cited By: 5

End-to-end change detection in satellite remote sensing imagery.

In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021) (pp. 4356–4359). (2021). Cited By; 3

 

Mokhtar Ferhi | Computer Science and Artificial Intelligence | Research Excellence Award

Dr. Mokhtar Ferhi | Computer Science and Artificial Intelligence | Research Excellence Award

University of Jendouba | Tunisia

Dr. Mokhtar Ferhi is a researcher at Université de Jendouba, Tunisia, specializing in heat transfer, fluid mechanics, magnetohydrodynamics (MHD), nanofluid convection, and numerical simulation methods, particularly the Lattice Boltzmann Method. He has authored 27 peer-reviewed publications, receiving 140 citations with an h-index of 6 (Scopus). His work focuses on entropy generation, energy optimization, and thermal performance enhancement in cavities and micro-heat exchangers. Ferhi collaborates internationally with experts across North Africa, Europe, and the Middle East, contributing to advances in energy-efficient thermal systems with applications in sustainable engineering and heat exchanger design.

Citation Metrics (Scopus)

400

300

200

100

0

Citations
140

Documents
27

h-index
6

🟦 Citations 🟥 Documents 🟩 h-index

View Google Scholar Profile
          View Scopus Profile
         View ORCID Profile

Featured Publications