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Akrem Sellami
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2020 – today
- 2024
- [j7]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) - 2023
- [j6]Akrem Sellami, Mohamed Farah, Mauro Dalla Mura:
SHCNet: A semi-supervised hypergraph convolutional networks based on relevant feature selection for hyperspectral image classification. Pattern Recognit. Lett. 165: 98-106 (2023) - [c15]Refka Hanachi, Akrem Sellami, Imed Riadh Farah, Mauro Dalla Mura:
DNGAE: Deep Neighborhood Graph Autoencoder for Robust Blind Hyperspectral Unmixing. ICCCI 2023: 84-96 - [c14]Maroua Mehri, Akrem Sellami, Salvatore Tabbone:
Historical Document Image Segmentation Combining Deep Learning and Gabor Features. ICDAR (4) 2023: 395-410 - 2022
- [j5]Akrem Sellami, Salvatore Tabbone:
Deep neural networks-based relevant latent representation learning for hyperspectral image classification. Pattern Recognit. 121: 108224 (2022) - [c13]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 - [c12]Akrem Sellami, Bishnu Sarker, Salvatore Tabbone, Marie-Dominique Devignes, Sabeur Aridhi:
A Semi-supervised Graph Deep Neural Network for Automatic Protein Function Annotation. IWBBIO (2) 2022: 153-166 - [c11]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 - 2021
- [c10]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 - [c9]Akrem Sellami, Salvatore Tabbone:
EDNets: Deep Feature Learning for Document Image Classification Based on Multi-view Encoder-Decoder Neural Networks. ICDAR (4) 2021: 318-332 - [c8]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 - 2020
- [j4]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) - [c7]Akrem Sellami, Salvatore Tabbone:
Video semantic segmentation using deep multi-view representation learning. ICPR 2020: 8133-8139 - [c6]Akrem Sellami, François-Xavier Dupé, Bastien Cagna, Hachem Kadri, Stéphane Ayache, Thierry Artières, Sylvain Takerkart:
Mapping individual differences in cortical architecture using multi-view representation learning. IJCNN 2020: 1-8 - [i2]Akrem Sellami, François-Xavier Dupé, Bastien Cagna, Hachem Kadri, Stéphane Ayache, Thierry Artières, Sylvain Takerkart:
Mapping individual differences in cortical architecture using multi-view representation learning. CoRR abs/2004.02804 (2020)
2010 – 2019
- 2019
- [j3]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) - [j2]Hakima Khelifi, Senlin Luo, Boubakr Nour, Akrem Sellami, Hassine Moungla, Syed Hassan Ahmed, Mohsen Guizani:
Bringing Deep Learning at the Edge of Information-Centric Internet of Things. IEEE Commun. Lett. 23(1): 52-55 (2019) - [i1]Mohammed Laroui, Akrem Sellami, Boubakr Nour, Hassine Moungla, Hossam Afifi, Sofiane Boukli Hacene:
Driving Path Stability in VANETs. CoRR abs/1906.08370 (2019) - 2018
- [j1]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) - [c5]Rawaa Hamdi, Akrem Sellami, Imed Riadh Farah:
An adaptive semantic dimensionality reduction approach for hyperspectral imagery classification. ATSIP 2018: 1-6 - [c4]Akrem Sellami, Mohamed Farah:
Comparative study of dimensionality reduction methods for remote sensing images interpretation. ATSIP 2018: 1-6 - [c3]Hakima Khelifi, Senlin Luo, Boubakr Nour, Akrem Sellami, Hassine Moungla, Farid Naït-Abdesselam:
An Optimized Proactive Caching Scheme Based on Mobility Prediction for Vehicular Networks. GLOBECOM 2018: 1-6 - [c2]Mohammed Laroui, Akrem Sellami, Boubakr Nour, Hassine Moungla, Hossam Afifi, Sofiane Boukli Hacene:
Driving Path Stability in VANETs. GLOBECOM 2018: 1-6 - 2017
- [b1]Akrem Sellami:
Interprétation sémantique d'images hyperspectrales basée sur la réduction adaptative de dimensionnalité. (Semantic interpretation of hyperspectral images based on the adaptative reduction of dimensionality). Ecole nationale supérieure Mines-Télécom Atlantique, France, 2017 - 2014
- [c1]Akrem Sellami, Karim Saheb Ettabaâ, Imed Riadh Farah, Basel Solaiman:
Interpretation of hyperspectral imagery based on hybrid dimensionality reduction methods. IPAS 2014: 1-6
Coauthor Index
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