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ORCIDAli Ben Abbes
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- affiliation: Ecole Nationale des Sciences de l'Informatique, la Manouba, Tunisia
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2020 – today
- 2023
[j13]Noureddine Jarray, Ali Ben Abbes, Imed Riadh Farah:
Machine learning for food security: current status, challenges, and future perspectives. Artif. Intell. Rev. 56(Supplement 3): 3853-3876 (2023)- [j12]Manel Rhif
, Ali Ben Abbes, Beatriz Martínez, Imed Riadh Farah:
Veg-W2TCN: A parallel hybrid forecasting framework for non-stationary time series using wavelet and temporal convolution network model. Appl. Soft Comput. 137: 110172 (2023) - [j11]Azza Abidi, Dino Ienco, Ali Ben Abbes, Imed Riadh Farah:
Combining 2D encoding and convolutional neural network to enhance land cover mapping from Satellite Image Time Series. Eng. Appl. Artif. Intell. 122: 106152 (2023) - [j10]Ali Ben Abbes, Raja Inoubli, Manel Rhif, Imed Riadh Farah:
Combining deep learning methods and multi-resolution analysis for drought forecasting modeling. Earth Sci. Informatics 16(2): 1811-1820 (2023) - [j9]Hanen Balti, Ali Ben Abbes, Yan-Fang Sang, Nedra Mellouli, Imed Riadh Farah:
Spatio-temporal heterogeneous graph using multivariate earth observation time series: Application for drought forecasting. Comput. Geosci. 179: 105435 (2023) - [c12]Farah Chouikhi, Ali Ben Abbes, Imed Riadh Farah:
Desertification Detection in Satellite Images Using Siamese Variational Autoencoder with Transfer Learning. ICCCI 2023: 513-525 - 2022
- [j8]Aya Ferchichi, Ali Ben Abbes, Vincent Barra, Imed Riadh Farah:
Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review. Ecol. Informatics 68: 101552 (2022) - [j7]Manel Rhif, Ali Ben Abbes, Beatriz Martínez, Rogier de Jong, Yan-Fang Sang, Imed Riadh Farah:
Detection of trend and seasonal changes in non-stationary remote sensing data: Case study of Tunisia vegetation dynamics. Ecol. Informatics 69: 101596 (2022) - [j6]Noureddine Jarray, Ali Ben Abbes, Manel Rhif, Hanen Dhaou, Mohamed Ouessar, Imed Riadh Farah:
SMETool: A web-based tool for soil moisture estimation based on Eo-Learn framework and Machine Learning methods. Environ. Model. Softw. 157: 105505 (2022) - [j5]Hanen Balti, Ali Ben Abbes, Nedra Mellouli, Imed Riadh Farah, Yan-Fang Sang, Myriam Lamolle:
Multidimensional architecture using a massive and heterogeneous data: Application to drought monitoring. Future Gener. Comput. Syst. 136: 1-14 (2022) - [j4]Noureddine Jarray, Ali Ben Abbes, Imed Riadh Farah:
A Novel Teacher-Student Framework for Soil Moisture Retrieval by Combining Sentinel-1 and Sentinel-2: Application in Arid Regions. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [c11]Farah Chouikhi, Manel Rhif, Ali Ben Abbes, Imed Riadh Farah:
Desertification Detection Based on Landsat Time-Series Images and Variational Auto-Encoder: Application in Jeffera, Tunisia. IGARSS 2022: 3688-3691 - [c10]Hanen Balti, Manel Rhif, Farah Chouikhi, Raja Inoubli, Azza Abidi, Noureddine Jarray, Ali Ben Abbes, Imed Riadh Farah:
SmartEarthTunisia: A Benchmark for Monitoring the SDGs USING Earth Observation Data and Deep Learning Techniques In Tunisia. IGARSS 2022: 7803-7806 - [c9]Noureddine Jarray, Ali Ben Abbes, Imed Riadh Farah:
A Machine Learning Framework for Cereal Yield Forecasting Using Heterogeneous Data. ISDA (2) 2022: 21-30 - 2021
- [c8]Manel Rhif, Ali Ben Abbes, Beatriz Martínez, Imed Riadh Farah:
An Improved Forecasting Model from Satellite Imagery Based on Optimum Wavelet Bases and Adam Optimized LSTM Methods. ICCCI 2021: 560-571 - [c7]Noureddine Jarray, Ali Ben Abbes, Imed Riadh Farah:
An Evaluation of Soil Moisture Retrieval Using Machine Learning Methods: Application in Arid Regions of Tunisia. IGARSS 2021: 6331-6334 - [c6]Hanen Balti, Nedra Mellouli, Ali Ben Abbes, Imed Riadh Farah, Yangfan Sang, Myriam Lamolle:
Enhancing Big Data Warehousing and Analytics for Spatio-Temporal Massive Data. ISD 2021 - 2020
- [j3]Hanen Balti, Ali Ben Abbes, Nedra Mellouli, Imed Riadh Farah, Yan-Fang Sang, Myriam Lamolle:
A review of drought monitoring with big data: Issues, methods, challenges and research directions. Ecol. Informatics 60: 101136 (2020) - [j2]Akrem Sellami, Ali Ben Abbes, Vincent Barra, Imed Riadh Farah:
Fused 3-D spectral-spatial deep neural networks and spectral clustering for hyperspectral image classification. Pattern Recognit. Lett. 138: 594-600 (2020) - [c5]Raja Inoubli, Ali Ben Abbes, Imed Riadh Farah, Vijay Singh, Tsegaye Tadesse, Mohammad Taghi Sattari:
A review of drought monitoring using remote sensing and data mining methods. ATSIP 2020: 1-6
2010 – 2019
- 2019
- [j1]Ali Ben Abbes, Mohamed Farah, Imed Riadh Farah, Vincent Barra:
A non-stationary NDVI time series modelling using triplet Markov chain. Int. J. Inf. Decis. Sci. 11(2): 163-179 (2019) - [c4]Ali Ben Abbes, Ramata Magagi, Kalifa Goita:
Soil Moisture Estimation From Smap Observations Using Long Short- Term Memory (LSTM). IGARSS 2019: 1590-1593 - 2016
- [b1]Ali Ben Abbes:
Modélisation de la non stationnarité des séries temporelles d'images satellites: Application à la prédiction des changements. Clermont Auvergne University, France, 2016 - 2015
- [c3]Ali Ben Abbes, Houcine Essid, Imed Riadh Farah, Vincent Barra:
Rare events detection in NDVI time-series using Jarque-Bera test. IGARSS 2015: 338-341 - 2014
- [c2]Ali Ben Abbes, Houcine Essid, Imed Riadh Farah, Vincent Barra:
A study of changes prediction by HMM with non-stationarity image data: Case of urban area. ATSIP 2014: 396-401 - [c1]Ali Ben Abbes, Houcine Essid, Imed Riadh Farah, Vincent Barra:
An adaptive multiplicative decomposition of non stationary multi-temporal satellite images: Application to urban changes detection. IPAS 2014: 1-7
Coauthor Index
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