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ORCIDImed Riadh Farah
Imed Riadh El Farah
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2020 – today
- 2024
[j51]Ali Ben Abbes, Noureddine Jarray, Imed Riadh Farah:
Advances in remote sensing based soil moisture retrieval: applications, techniques, scales and challenges for combining machine learning and physical models. Artif. Intell. Rev. 57(9): 224 (2024)- [j50]Aya Ferchichi
, Ali Ben Abbes, Vincent Barra, Manel Rhif, Imed Riadh Farah:
Multi-attention Generative Adversarial Network for multi-step vegetation indices forecasting using multivariate time series. Eng. Appl. Artif. Intell. 128: 107563 (2024) - [j49]Refka Hanachi, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
Graph feature fusion driven by deep autoencoder for advanced hyperspectral image unmixing. Knowl. Based Syst. 299: 112087 (2024) - [j48]Refka Hanachi, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
Multi-view graph representation learning for hyperspectral image classification with spectral-spatial graph neural networks. Neural Comput. Appl. 36(7): 3737-3759 (2024) - [j47]Azza Abidi, Dino Ienco, Ali Ben Abbes, Imed Riadh Farah:
Orthrus: multi-scale land cover mapping from satellite image time series via 2D encoding and convolutional neural network. Neural Comput. Appl. 36(30): 19247-19265 (2024) - [j46]Hanen Balti, Ali Ben Abbes, Imed Riadh Farah:
A Bi-GRU-based encoder-decoder framework for multivariate time series forecasting. Soft Comput. 28(9-10): 6775-6786 (2024) - [j45]Raja Inoubli, Daniel Enrique Constantino-Recillas, Alejandro Monsiváis-Huertero, Lilia Bennaceur Farah, Imed Riadh Farah:
Assessment of Surface Scattering Models Within the Water Cloud Model Toward Soil Moisture Retrievals Using Sentinel-1 and Sentinel-2 Images. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 17412-17429 (2024) - [c92]Raja Inoubli, Daniel Enrique Constantino-Recillas, Alejandro Monsiváis-Huertero, Lilia Bennaceur Farah, Imed Riadh Farah:
Computational methods to retrieve soil moisture using remote sensing data: A review. ATSIP 2024: 77-82 - [c91]Farah Chouikhi, Ali Ben Abbes, Imed Riadh Farah:
TALDS: A Transfer-Active Learning-Driven Siamese Network for Bi-temporal Image Classification. ATSIP 2024: 471-476 - [c90]Mariem Ayad, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
Geometric Deep Learning Techniques for Analyzing Brain 3D Meshes. ATSIP 2024: 477-482 - [c89]Refka Hanachi, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
Advanced graph deep learning for High-dimensional image analysis: challenges and opportunities. ATSIP 2024: 488-493 - [c88]Azza Abidi, Dino Ienco, Ali Ben Abbes, Imed Riadh Farah:
Multi-Scale Classification of Sentinel-2 Images for Land Cover Mapping Using Two-Branch Convolutional Neural Network. IGARSS 2024: 4109-4113 - [c87]Farah Chouikhi, Ali Ben Abbes, Imed Riadh Farah:
Monitoring Desertification in Tunisia Using Modis Ecological Indicators and Machine Learning. IGARSS 2024: 10006-10010 - [c86]Raja Inoubli, Daniel Enrique Constantino-Recillas, Alejandro Monsiváis-Huertero, Lilia Bennaceur Farah, Imed Riadh Farah:
Predicting C-band backscattering coefficient using the water cloud model and optical vegetation indices. IGARSS 2024: 10629-10633 - 2023
- [j44]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) - [j43]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) - [j42]Manel Khazri Khlifi, Wadii Boulila, Imed Riadh Farah:
Graph-based deep learning techniques for remote sensing applications: Techniques, taxonomy, and applications - A comprehensive review. Comput. Sci. Rev. 50: 100596 (2023) - [j41]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) - [j40]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) - [j39]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) - [j38]Abir Bousmina, Mouna Selmi, Mohamed Amine Ben Rhaiem, Imed Riadh Farah:
A Hybrid Approach Based on GAN and CNN-LSTM for Aerial Activity Recognition. Remote. Sens. 15(14): 3626 (2023) - [c85]Refka Hanachi, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
DNGAE: Deep Neighborhood Graph Autoencoder for Robust Blind Hyperspectral Unmixing. ICCCI 2023: 84-96 - [c84]Farah Chouikhi, Ali Ben Abbes, Imed Riadh Farah:
Desertification Detection in Satellite Images Using Siamese Variational Autoencoder with Transfer Learning. ICCCI 2023: 513-525 - [c83]Raja Inoubli, Daniel Enrique Constantino-Recillas, Alejandro Monsiváis-Huertero, Lilia Bennaceur Farah, Imed Riadh Farah:
Evaluation of Two Surface Scattering Models Within the Water Cloud Model Over an Agricultural Area in Mexico and Synergistic Use of Sentinel-1 and Sentinel-2 Images. IGARSS 2023: 3213-3216 - [c82]Mohamed Louay Rabah, Nedra Mellouli, Imed Riadh Farah:
Interpolation and Prediction of Piezometric Multivariate Time Series Based on Data Augmentation and Transformers. IntelliSys (2) 2023: 327-344 - [c81]Zouhayra Ayadi, Wadii Boulila, Imed Riadh Farah:
Modeling Complex Object Changes in Satellite Image Time-Series: Approach based on CSP and Spatiotemporal Graphs. KES 2023: 2467-2476 - [c80]Yosra Hajjaji, Ayyub Alzahem, Wadii Boulila, Imed Riadh Farah, Anis Koubaa:
Sustainable Palm Tree Farming: Leveraging IoT and Multi-Modal Data for Early Detection and Mapping of Red Palm Weevil. KES 2023: 4952-4962 - [i5]Zouhayra Ayadi, Wadii Boulila, Imed Riadh Farah:
Modeling Complex Object Changes in Satellite Image Time-Series: Approach based on CSP and Spatiotemporal Graph. CoRR abs/2305.15091 (2023) - [i4]Yosra Hajjaji, Ayyub Alzahem, Wadii Boulila, Imed Riadh Farah, Anis Koubaa:
Sustainable Palm Tree Farming: Leveraging IoT and Multi-Modal Data for Early Detection and Mapping of Red Palm Weevil. CoRR abs/2306.16862 (2023) - 2022
- [j37]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) - [j36]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) - [j35]Zouhayra Ayadi, Wadii Boulila, Imed Riadh Farah, Aurélie Leborgne, Pierre Gançarski:
Resolution methods for constraint satisfaction problem in remote sensing field: A survey of static and dynamic algorithms. Ecol. Informatics 69: 101607 (2022) - [j34]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) - [j33]Manel Chehibi, Ahlem Ferchichi, Imed Riadh Farah:
Representing and modeling spatio-temporal uncertainty using belief function theory in flood extent mapping. Expert Syst. Appl. 209: 118212 (2022) - [j32]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) - [j31]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) - [j30]Slim Namouchi, Imed Riadh Farah:
Graph-Based Classification and Urban Modeling of Laser Scanning and Imagery: Toward 3D Smart Web Services. Remote. Sens. 14(1): 114 (2022) - [j29]Wadii Boulila, Manel Khazri Khlifi, Adel Ammar, Anis Koubaa, Bilel Benjdira, Imed Riadh Farah:
A Hybrid Privacy-Preserving Deep Learning Approach for Object Classification in Very High-Resolution Satellite Images. Remote. Sens. 14(18): 4631 (2022) - [c79]Mariem Ayed, Refka Hanachi, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
A deep learning approach based on morphological profiles for Hyperspectral Image unmixing. ATSIP 2022: 1-6 - [c78]Ikram Chourib, Gwenaël Guillard, Imed Riadh Farah, Basel Solaiman:
Structured Case Base Knowledge using Unsupervised Learning. ATSIP 2022: 1-6 - [c77]Imen Gatfaoui, Basel Solaiman, Imed Riadh Farah:
Model Based Anomaly Detection in High Dimensional DATA. ATSIP 2022: 1-6 - [c76]Mohamed Sahbi Landolsi, Yemna Sayeb, Wajih Krimi, Imed Riadh El Farah:
Improving Smart City Frameworks based on Enterprise Architecture with territorial governance to manage covid -19 crisis. ATSIP 2022: 1-6 - [c75]Wissal Ben Marzouka, Basel Solaiman, Mohamed Farah, Imed Riadh Farah:
Hypothetical reasoning method based on hypothetical cases. ATSIP 2022: 1-6 - [c74]Manel Chehibi, Ahlem Ferchichi, Imed Riadh Farah:
An Intelligent System for Managing Uncertain Temporal Flood Events. BELIEF 2022: 184-193 - [c73]Nedra Mellouli, Mohamed Louay Rabah, Imed Riadh Farah:
Transformers-based time series forecasting for piezometric level prediction. EAIS 2022: 1-6 - [c72]Mohamed Louay Rabah, Nedra Mellouli, Imed Riadh Farah:
Modèle de prédiction de niveau piézométrique basé sur Transformers. EGC 2022: 305-312 - [c71]Oumayma Bounouh, Ana Maria Tarquis, Imed Riadh Farah:
Novel Method for Combining NDVI Time Series Forecasting Models. IGARSS 2022: 2355-2357 - [c70]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 - [c69]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 - [c68]Noureddine Jarray, Ali Ben Abbes, Imed Riadh Farah:
A Machine Learning Framework for Cereal Yield Forecasting Using Heterogeneous Data. ISDA (2) 2022: 21-30 - [c67]Yosra Hajjaji, Wadii Boulila, Imed Riadh Farah:
Leveraging Artificial Intelligence Techniques for Smart Palm Tree Detection: A Decade Systematic Review. KES 2022: 2823-2832 - [c66]Refka Hanachi, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
Multi Spectral-Spatial Gabor Feature Fusion Based On End-To-End Deep Learning For Hyperspectral Image Classification. WHISPERS 2022: 1-6 - [i3]Yosra Hajjaji, Wadii Boulila, Imed Riadh Farah:
Leveraging Artificial Intelligence Techniques for Smart Palm Tree Detection: A Decade Systematic Review. CoRR abs/2209.05282 (2022) - 2021
- [j28]Imen Chebbi, Nedra Mellouli, Imed Riadh Farah, Myriam Lamolle:
Big Remote Sensing Image Classification Based on Deep Learning Extraction Features and Distributed Spark Frameworks. Big Data Cogn. Comput. 5(2): 21 (2021) - [j27]Yosra Hajjaji, Wadii Boulila, Imed Riadh Farah, Imed Romdhani, Amir Hussain:
Big data and IoT-based applications in smart environments: A systematic review. Comput. Sci. Rev. 39: 100318 (2021) - [j26]Bouthayna Msellmi, Daniele Picone, Zouhaier Ben Rabah, Mauro Dalla Mura, Imed Riadh Farah:
Sub-Pixel Mapping Model Based on Total Variation Regularization and Learned Spatial Dictionary. Remote. Sens. 13(2): 190 (2021) - [c65]Refka Hanachi, Akrem Sellami, Imed Riadh Farah:
BS-GAENets: Brain-Spatial Feature Learning Via a Graph Deep Autoencoder for Multi-modal Neuroimaging Analysis. VISIGRAPP (Revised Selected Papers) 2021: 303-327 - [c64]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 - [c63]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 - [c62]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 - [c61]Yosra Hajjaji, Wadii Boulila, Imed Riadh Farah:
An improved tile-based scalable distributed management model of massive high-resolution satellite images. KES 2021: 2931-2942 - [c60]Zouhayra Ayadi, Wadii Boulila, Imed Riadh Farah:
A Hybrid APM-CPGSO Approach for Constraint Satisfaction Problem Solving: Application to Remote Sensing. KES 2021: 3403-3412 - [c59]Refka Hanachi, Akrem Sellami, Imed Riadh Farah:
Interpretation of Human Behavior from Multi-modal Brain MRI Images based on Graph Deep Neural Networks and Attention Mechanism. VISIGRAPP (4: VISAPP) 2021: 56-66 - [i2]Yosra Hajjaji, Wadii Boulila, Imed Riadh Farah:
An improved tile-based scalable distributed management model of massive high-resolution satellite images. CoRR abs/2105.04731 (2021) - [i1]Zouhayra Ayadi, Wadii Boulila, Imed Riadh Farah:
A Hybrid APM-CPGSO Approach for Constraint Satisfaction Problem Solving: Application to Remote Sensing. CoRR abs/2106.05193 (2021) - 2020
- [j25]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) - [j24]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) - [c58]Marwen Bouabid, Mohamed Farah, Imed Riadh Farah:
Suspicious Local Event Detection in Social Media and Remote Sensing: Towards a Geosocial Dataset Construction. ATSIP 2020: 1-6 - [c57]Ikram Chourib, Gwenaël Guillard, Makram Mestiri, Basel Solaiman, Imed Riadh Farah:
Case-Based Reasoning: Problems And Importance Of Similarity Measure. ATSIP 2020: 1-6 - [c56]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 - [c55]Salim Klibi, Kais Tounsi, Zouhaier Ben Rabah, Basel Solaiman, Imed Riadh Farah:
Soil salinity prediction using a machine learning approach through hyperspectral satellite image. ATSIP 2020: 1-6 - [c54]Bouthayna Msellmi, Daniele Picone, Zouhaier Ben Rabah, Mauro Dalla Mura, Imed Riadh Farah:
Sub-pixel Mapping Method based on Total Variation Minimization and Spectral Dictionary. ATSIP 2020: 1-7 - [c53]Bouthayna Msellmi, Daniele Picone, Zouhaier Ben Rabah, Mauro Dalla Mura, Imed Riadh Farah:
Sub-Pixel Mapping Method Based on K-SVD Dictionary Learning and Total Variation Minimization. IGARSS 2020: 2823-2826
2010 – 2019
- 2019
- [j23]Akrem Sellami, Mohamed Farah, Imed Riadh Farah, Basel Solaiman:
Hyperspectral imagery classification based on semi-supervised 3-D deep neural network and adaptive band selection. Expert Syst. Appl. 129: 246-259 (2019) - [j22]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) - [j21]Wassim Messaoudi, Mohamed Farah, Imed Riadh Farah:
Fuzzy Spatio-Spectro-Temporal Ontology for Remote Sensing Image Annotation and Interpretation: Application to Natural Risks Assessment. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(5): 815-840 (2019) - [j20]Yaakoub Boualleg, Mohamed Farah, Imed Riadh Farah:
Remote Sensing Scene Classification Using Convolutional Features and Deep Forest Classifier. IEEE Geosci. Remote. Sens. Lett. 16(12): 1944-1948 (2019) - [j19]Fethi Ghazouani, Imed Riadh Farah, Basel Solaiman:
A Multi-Level Semantic Scene Interpretation Strategy for Change Interpretation in Remote Sensing Imagery. IEEE Trans. Geosci. Remote. Sens. 57(11): 8775-8795 (2019) - [c52]Imen Chebbi, Nedra Mellouli, Myriam Lamolle, Imed Riadh Farah:
Deep Learning Analysis for Big Remote Sensing Image Classification. KDIR 2019: 355-362 - [c51]Hanen Balti, Nedra Mellouli, Imen Chebbi, Imed Riadh Farah, Myriam Lamolle:
Deep Semantic Feature Detection from Multispectral Satellite Images. KDIR 2019: 458-466 - [c50]Bouthayna Msellmi, Daniele Picone, Mauro Dalla Mura, Zouhaier Ben Rabah, Imed Riadh Farah:
Isotropic Total Variation Minimization for Sub-Pixel Mapping. IGARSS 2019: 3325-3328 - [c49]Slim Namouchi, Bruno Vallet, Imed Riadh Farah, Haythem Ismail:
Piecewise Horizontal 3D Roof Reconstruction from Aerial Lidar. IGARSS 2019: 8992-8995 - 2018
- [j18]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
Corrigendum to "Propagating aleatory and epistemic uncertainty in land cover change prediction process" [Ecol. Inform. 37, 24-37]. Ecol. Informatics 43: 231 (2018) - [j17]Wadii Boulila, Imed Riadh Farah, Amir Hussain:
A novel decision support system for the interpretation of remote sensing big data. Earth Sci. Informatics 11(1): 31-45 (2018) - [j16]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
Reducing uncertainties in land cover change models using sensitivity analysis. Knowl. Inf. Syst. 55(3): 719-740 (2018) - [j15]Ines Ben Slimene Ben Amor, Nesrine Chehata, Jean-Stéphane Bailly, Imed Riadh Farah, Philippe Lagacherie:
Parcel-Based Active Learning for Large Extent Cultivated Area Mapping. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 11(1): 79-88 (2018) - [j14]Akrem Sellami, Mohamed Farah, Imed Riadh Farah, Basel Solaiman:
Hyperspectral Imagery Semantic Interpretation Based on Adaptive Constrained Band Selection and Knowledge Extraction Techniques. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 11(4): 1337-1347 (2018) - [c48]Imen Chebbi, Wadii Boulila, Nedra Mellouli, Myriam Lamolle, Imed Riadh Farah:
A comparison of big remote sensing data processing with Hadoop MapReduce and Spark. ATSIP 2018: 1-4 - [c47]Fethi Ghazouani, Imed Riadh Farah, Basel Solaiman:
Qualitative semantic spatio-temporal reasoning based on description logics for modeling dynamics of spatio-temporal objects in satellite images. ATSIP 2018: 1-6 - [c46]Yosra Hajjaji, Imed Riadh Farah:
Performance investigation of selected NoSQL databases for massive remote sensing image data storage. ATSIP 2018: 1-6 - [c45]Rawaa Hamdi, Akrem Sellami, Imed Riadh Farah:
An adaptive semantic dimensionality reduction approach for hyperspectral imagery classification. ATSIP 2018: 1-6 - [c44]Manel Rhif, Hazem Wannous, Imed Riadh Farah:
Action Recognition from 3D Skeleton Sequences using Deep Networks on Lie Group Features. ICPR 2018: 3427-3432 - [c43]Bouthayna Msellmi, Zouhaier Ben Rabah, Imed Riadh Farah:
A GRAPH BASED MODEL FOR SUB-PIXEL OBJECTS RECOGNITION. IGARSS 2018: 7070-7073 - [c42]Khadhar Meriem, Mestiri Makram, Imed Riadh Farah:
Designing Human Brain Interface Model for Interactive Cognitive Learning in an Immersive System with Neurofeedback. IEEE Conf. on Intelligent Systems 2018: 645-651 - [c41]Khadhar Meriem, Mestiri Makram, Imed Riadh Farah:
Virtual and Augmented Reality in the Valuation of the Tunisian Cultural Heritage: Application to Thysdrus (ElJem) Amphitheater. IEEE Conf. on Intelligent Systems 2018: 652-654 - 2017
- [j13]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
Propagating aleatory and epistemic uncertainty in land cover change prediction process. Ecol. Informatics 37: 24-37 (2017) - [j12]Wadii Boulila, Zouhayra Ayadi, Imed Riadh Farah:
Sensitivity analysis approach to model epistemic and aleatory imperfection: Application to Land Cover Change prediction model. J. Comput. Sci. 23: 58-70 (2017) - [j11]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
Towards an uncertainty reduction framework for land-cover change prediction using possibility theory. Vietnam. J. Comput. Sci. 4(3): 195-209 (2017) - [c40]Khitem Amiri, Mohamed Farah, Imed Riadh Farah:
Fuzzy hypergraph of concepts for semantic annotation of remotely sensed images. ATSIP 2017: 1-8 - [c39]Malek Boujebli, Hassen Drira, Makram Mestiri, Imed Riadh Farah:
Rate invariant action recognition in Lie algebra. ATSIP 2017: 1-7 - [c38]Oumayma Bounouh, Houcine Essid, Imed Riadh Farah:
Prediction of land use/land cover change methods: A study. ATSIP 2017: 1-7 - 2016
- [j10]Mohamed Farah, Hafed Nefzi, Imed Riadh Farah:
A similarity-based framework for the alignment of an ontology for remote sensing. Comput. Geosci. 96: 202-207 (2016) - [c37]Imen Chebbi, Wadii Boulila, Imed Riadh Farah:
Improvement of satellite image classification: Approach based on Hadoop/MapReduce. ATSIP 2016: 31-34 - [c36]Zouhaier Ben Rabah, Imed Riadh Farah:
Evaluation and predictability of water erosion based on spectral information analysis. ATSIP 2016: 533-536 - [c35]Fethi Ghazouani, Wassim Messaoudi, Imed Riadh Farah:
Towards an ontological conceptualization for understanding the dynamics of spatio-temporal objects. ATSIP 2016: 543-548 - [c34]Zouhayra Ayadi, Wadii Boulila, Imed Riadh Farah:
Sensitivity analysis of land cover change prediction model in the presence of aleatory and epistemic imperfection. ATSIP 2016: 549-554 - [c33]Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur, Imed Riadh Farah:
On the effects of vegetation on radar backscattering. ATSIP 2016: 561-566 - [c32]Mohamed Farah, Khitem Amiri, Imed Riadh Farah:
Graph of visual words for semantic annotation of remote sensing images. ATSIP 2016: 606-612 - [c31]Bouthayna Msellmi, Zouhaier Ben Rabah, Imed Riadh Farah:
Super-resolution algorithm based on sub-pixels spatial Correlation for hyperspectral image classification. ATSIP 2016: 613-615 - 2015
- [c30]Fethi Ghazouani, Wassim Messaoudi, Imed Riadh Farah:
A Multi-level Ontological Approach for Change Monitoring in Remotely Sensed Imagery. KEOD 2015: 435-440 - [c29]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
An Intelligent Possibilistic Approach to Reduce the Effect of the Imperfection Propagation on Land Cover Change Prediction. ICCCI (2) 2015: 520-529 - [c28]Imen Chebbi, Wadii Boulila, Imed Riadh Farah:
Big Data: Concepts, Challenges and Applications. ICCCI (2) 2015: 638-647 - [c27]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 - [c26]Ines Ben Slimene Ben Amor, Nesrine Chehata, Philippe Lagacherie, Jean-Stéphane Bailly, Imed Riadh Farah:
Can we automatically choose best uncertainty heuristics for large margin active learning? IGARSS 2015: 4360-4363 - [c25]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
Using Evidence Theory in Land Cover Change Prediction to Model Imperfection Propagation with Correlated Inputs Parameters. IJCCI (FCTA) 2015: 47-56 - [c24]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
Improvement of LCC Prediction Modeling Based on Correlated Parameters and Model Structure Uncertainty Propagation. IJCCI (Selected Papers) 2015: 270-290 - [c23]Fedia Ghedass, Imed Riadh Farah:
An improved classification of hyperspectral imaging based on spectral signature and gray level co-occurrence matrix. SAGEO 2015: 269-282 - 2014
- [j9]Wadii Boulila, Amine Bouatay, Imed Riadh Farah:
A Probabilistic Collocation Method for the Imperfection Propagation: Application to Land Cover Change Prediction. J. Multim. Process. Technol. 5(1): 12-32 (2014) - [c22]Wassim Messaoudi, Imed Riadh Farah, Basel Solaiman:
A new ontology for semantic annotation of remotely sensed images. ATSIP 2014: 36-41 - [c21]Hafed Nefzi, Mohamed Farah, Imed Riadh Farah, Basel Solaiman:
A critical analysis of lifecycles and methods for ontology construction and evaluation. ATSIP 2014: 48-53 - [c20]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 - [c19]Hafed Nefzi, Mohamed Farah, Imed Riadh Farah, Basel Solaiman:
A Semi-automatic Mapping Selection in the Ontology Alignment Process. KEOD 2014: 459-466 - [c18]Amine Bouatay, Wadii Boulila, Imed Riadh Farah:
An Approach for Imperfection Propagation: Application to Land Cover Change Prediction. ICAISC (1) 2014: 637-648 - [c17]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 - [c16]Ines Ben Slimene Ben Amor, Nesrine Chehata, Imed Riadh Farah, Philippe Lagacherie:
Uncertainty heuristics of large margin active learning for hyperspectral image classification. IPAS 2014: 1-6 - [c15]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
Parameter and structural model imperfection propagation using evidence theory in land cover change prediction. IPAS 2014: 1-6 - [c14]B. Mselmi, Zouhaier Ben Rabah, Imed Riadh Farah, Basel Solaiman:
Multi-resolution and multi-spectral analysis for satellite images classification with fuzzy spatial relationships. IPAS 2014: 1-6 - [c13]Hafedh Nefzi, Mohamed Farah, Imed Riadh Farah, Basel Solaiman:
Towards a new ontology matching approach based on multi-criteria analysis methods. IPAS 2014: 1-7 - [c12]Akrem Sellami, Karim Saheb Ettabaâ, Imed Riadh Farah, Basel Solaiman:
Interpretation of hyperspectral imagery based on hybrid dimensionality reduction methods. IPAS 2014: 1-6 - 2013
- [j8]Selim Hemissi, Imed Riadh Farah, Karim Saheb Ettabaâ, Basel Solaiman:
Multi-Spectro-Temporal Analysis of Hyperspectral Imagery Based on 3-D Spectral Modeling and Multilinear Algebra. IEEE Trans. Geosci. Remote. Sens. 51(1): 199-216 (2013) - [c11]Ahlem Ferchichi, Wadii Boulila, Imed Riadh Farah:
An Approach based on Adaptive Decision Tree for Land Cover Change Prediction in Satellite Images. KDIR/KMIS 2013: 82-90 - [c10]Selim Hemissi, Imed Riadh Farah:
A Multi-features Fusion of Multi-temporal Hyperspectral Images using a Cooperative GDD/SVM Method. ICPRAM 2013: 681-685 - [c9]Selim Hemissi, Imed Riadh Farah:
A data-noise tolerant method for multi-temporal hyperspectral images classification. WHISPERS 2013: 1-4 - 2012
- [c8]Selim Hemissi, Imed Riadh Farah, Karim Saheb Ettabaâ, Basel Solaiman:
A robust Evidential Fisher Discriminant for multi-temporal hyperspectral images classification. IGARSS 2012: 4275-4278 - [c7]Wadii Boulila, Karim Saheb Ettabaâ, Imed Riadh Farah, Basel Solaiman:
High level adaptive fusion approach: application to land cover change prediction in satellite image databases. SAC 2012: 21-22 - 2011
- [j7]Wadii Boulila, Imed Riadh Farah, Karim Saheb Ettabaâ, Basel Solaiman, Henda Ben Ghézala:
A data mining based approach to predict spatiotemporal changes in satellite images. Int. J. Appl. Earth Obs. Geoinformation 13(3): 386-395 (2011) - [j6]Wadii Boulila, Imed Riadh Farah:
Multi-Approach Satellite Images Fusion Based on Blind Sources Separation. Int. J. Image Graph. 11(1): 117-136 (2011) - [j5]Wadii Boulila, Imed Riadh Farah, Karim Saheb Ettabaâ, Basel Solaiman:
Combining Decision Fusion and Uncertainty Propagation to Improve Land Cover Change Prediction in Satellite Image Databases. J. Multim. Process. Technol. 2(3): 127-139 (2011) - [j4]Zouhaier Ben Rabah, Imed Riadh Farah, Grégoire Mercier, Basel Solaiman:
A New Method to Change Illumination Effect Reduction Based on Spectral Angle Constraint for Hyperspectral Image Unmixing. IEEE Geosci. Remote. Sens. Lett. 8(6): 1110-1114 (2011) - 2010
- [c6]Wadii Boulila, Imed Riadh Farah, Karim Saheb Ettabaâ, Basel Solaiman, Henda Ben Ghézala:
Spatio-Temporal Modeling for Knowledge Discovery in Satellite Image Databases. CORIA 2010: 35-49
2000 – 2009
- 2008
- [j3]Karim Saheb Ettabaâ, Imed Riadh Farah, Soulaimen Basel, Mohamed Ben Ahmed:
Toward a Multi-temporal Approach for Satellite Image Interpretation. Int. Arab J. Inf. Technol. 5(3): 281-287 (2008) - [j2]Imed Riadh Farah, Wadii Boulila, Karim Saheb Ettabaâ, Basel Solaiman, Mohamed Ben Ahmed:
Interpretation of Multisensor Remote Sensing Images: Multiapproach Fusion of Uncertain Information. IEEE Trans. Geosci. Remote. Sens. 46(12): 4142-4152 (2008) - [j1]Imed Riadh Farah, Wadii Boulila, Karim Saheb Ettabaâ, Mohamed Ben Ahmed:
Multiapproach System Based on Fusion of Multispectral Images for Land-Cover Classification. IEEE Trans. Geosci. Remote. Sens. 46(12): 4153-4161 (2008) - 2007
- [c5]Ines Hamdi, Imed Riadh Farah, Mohamed Ben Ahmed:
Analyzing and Dynamic Modeling of Molecular Interactions Networks Based on Multi-agent Systems. BIOCOMP 2007: 76-82 - [c4]Karim Saheb Ettabaâ, Imed Riadh Farah, Mohamed Ben Ahmed, Soulaiman Bassel:
Toward a semi-automatic interpretation of scenes issued from multisensor satellite images. IGARSS 2007: 3104-3108 - 2005
- [c3]Ines Hamdi, Imed Riadh Farah, Mohmed B. Ahmed:
Analysing spatial-temporal data based on generic GIS. AICCSA 2005: 102 - 2003
- [c2]Imed Riadh Farah, Mohamed Ben Ahmed, Mohamed Rached Boussema:
Multispectral satellite image analysis based on the method of blind separation and fusion of sources. IGARSS 2003: 3638-3640 - 2002
- [c1]Imed Riadh Farah, Mohamed Ben Ahmed:
Satellite image analysis based on the method of blind separation of sources for the extraction of information. IGARSS 2002: 919-921
Coauthor Index
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