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Oumayma Bounouh

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Qualifications: Ph.D., National school of computer science, La Manouba university, MRes, National School of Engineering of Tunis, Engineering Diploma, TIME University, Tunisia.

Biography

Oumayma Bounouh holds a PhD from La Manouba University and a master of research from ElManar University . She is currently an Assistant Professor at the Mediterranean Institute of Technology where she teaches Data structures and algorithms and Introduction to AI and ML courses. After having worked on data science and remote sensing, she is now concentrating on monitoring and forecasting the Tunisian green cover changes for both agricultural and forest areas.

Areas of Expertise

Data science Time series analysis Machine Learning Forecasting Artificial intelligence Data Visualization

Research Interest

Remote sensing SDG Vegetation cover changes

Ben Abbes, A., Bounouh, O., Farah, I. R., de Jong, R., & Martínez, B. (2018). Comparative study of three satellite image time-series decomposition methods for vegetation change detection. European Journal of Remote Sensing, 51(1), 607-615.    Bounouh, O., Essid, H., Tarquis, A. M., & Farah, I. R. (2021). Phenology as accuracy metrics for vegetation index forecasting over Tunisian forest and cereal cover types. International Journal of Remote Sensing, 42(12), 4644-4671.     Bounouh, O., Tarquis, A. M., & Farah, I. R. (2022, July). Novel Method for Combining NDVI Time Series Forecasting Models. In IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 2355-2357). IEEE.     Bounouh, O., Tarquis, A. M., & Riadh Farah, I. (2022, May). Investigation of climate change impact on olive trees in Tunisia via MODIS LST and NDVI products and correlation measures. In EGU General Assembly Conference Abstracts (pp. EGU22-13255).

  • Classical Mechanics
  • Electromagnetism
  • Wind Energy
  • Engineering Vibration
  • Machine Dynamics
  • Applied Multibody Dynamics
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