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ORCIDRohaifa Khaldi
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2020 – today
- 2024
[j5]Rohaifa Khaldi
, Siham Tabik, Sergio Puertas-Ruíz, Julio Peñas de Giles, José Antonio Hódar Correa, Regino Zamora, Domingo Alcaraz-Segura:
Individual mapping of large polymorphic shrubs in high mountains using satellite images and deep learning. Int. J. Appl. Earth Obs. Geoinformation 134: 104191 (2024)- [j4]José Rodríguez-Ortega, Rohaifa Khaldi, Domingo Alcaraz-Segura, Siham Tabik:
Bidirectional Recurrent Imputation and Abundance Estimation of LULC Classes With MODIS Multispectral Time-Series and Geo-Topographic and Climatic Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 4626-4645 (2024) - [i5]Rohaifa Khaldi, Siham Tabik, Sergio Puertas-Ruíz, Julio Peñas de Giles, José Antonio Hódar Correa, Regino Zamora, Domingo Alcaraz-Segura:
Shrub of a thousand faces: an individual segmentation from satellite images using deep learning. CoRR abs/2401.17985 (2024) - [i4]Aymane Khaldi, Rohaifa Khaldi:
Recognition of Harmful Phytoplankton from Microscopic Images using Deep Learning. CoRR abs/2409.12900 (2024) - [i3]Rohaifa Khaldi, Domingo Alcaraz-Segura, Ignacio Sánchez-Herrera, Javier Martínez-López, Carlos Javier Navarro, Siham Tabik:
On Large Uni- and Multi-modal Models for Unsupervised Classification of Social Media Images: Nature's Contribution to People as a case study. CoRR abs/2410.00275 (2024) - 2023
- [j3]Rohaifa Khaldi, Abdellatif El Afia, Raddouane Chiheb, Siham Tabik:
What is the best RNN-cell structure to forecast each time series behavior? Expert Syst. Appl. 215: 119140 (2023) - [i2]José Rodríguez-Ortega, Rohaifa Khaldi, Domingo Alcaraz-Segura, Siham Tabik:
Deep Learning for blind spectral unmixing of LULC classes with MODIS multispectral time series and ancillary data. CoRR abs/2310.07223 (2023) - 2022
- [i1]Rohaifa Khaldi, Abdellatif El Afia, Raddouane Chiheb, Siham Tabik:
What is the best RNN-cell structure for forecasting each time series behavior? CoRR abs/2203.07844 (2022)
2010 – 2019
- 2019
- [j2]Rohaifa Khaldi, Abdellatif El Afia, Raddouane Chiheb:
Performance prediction of pharmaceutical suppliers: comparative study between DEA-ANFIS-PSO and DEA-ANFIS-GA. Int. J. Comput. Appl. Technol. 60(4): 317-325 (2019) - [j1]Rohaifa Khaldi, Abdellatif El Afia, Raddouane Chiheb:
Forecasting of BTC volatility: comparative study between parametric and nonparametric models. Prog. Artif. Intell. 8(4): 511-523 (2019) - [c5]Rohaifa Khaldi, Abdellatif El Afia, Raddouane Chiheb:
Impact of Multistep Forecasting Strategies on Recurrent Neural Networks Performance for Short and Long Horizons. BDIoT 2019 - 2018
- [c4]Rohaifa Khaldi, Raddouane Chiheb, Abdellatif El Afia:
Feedforward and Recurrent Neural Networks for Time Series Forecasting: Comparative Study. LOPAL 2018: 18:1-18:6 - [c3]Rohaifa Khaldi, Abdellatif El Afia, Raddouane Chiheb, Rdouan Faizi:
Forecasting of Bitcoin Daily Returns with EEMD-ELMAN based Model. LOPAL 2018: 20:1-20:6 - 2017
- [c2]Rohaifa Khaldi, Abdellatif El Afia, Raddouane Chiheb, Rdouan Faizi:
Artificial Neural Network Based Approach for Blood Demand Forecasting: Fez Transfusion Blood Center Case Study. BDCA 2017: 59:1-59:6 - [c1]Rohaifa Khaldi, Raddouane Chiheb, Abdellatif El Afia, Adil Akaaboune, Rdouan Faizi:
Prediction of Supplier Performance: A Novel Dea-Anfis Based Approach. BDCA 2017: 60:1-60:6
Coauthor Index
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