Interpretation of hyperspectral imagery based on hybrid dimensionality reduction methods. - Akrem Sellami; Karim Saheb Ettabaâ; Imed Riadh Farah; Basel Solaiman (IPAS, 2014)

Interprétation sémantique d'images hyperspectrales basée sur la réduction adaptative de dimensionnalité. (Semantic interpretation of hyperspectral images based on the adaptative reduction of dimensionality). - Akrem Sellami (2017)

An adaptive semantic dimensionality reduction approach for hyperspectral imagery classification. - Rawaa Hamdi; Akrem Sellami; Imed Riadh Farah (ATSIP, 2018)

Comparative study of dimensionality reduction methods for remote sensing images interpretation. - Akrem Sellami; Mohamed Farah 001 (ATSIP, 2018)

An Optimized Proactive Caching Scheme Based on Mobility Prediction for Vehicular Networks. - Hakima Khelifi; Senlin Luo; Boubakr Nour; Akrem Sellami; Hassine Moungla; Farid Naït-Abdesselam (GLOBECOM, 2018)

Driving Path Stability in VANETs. - Mohammed Laroui; Akrem Sellami; Boubakr Nour; Hassine Moungla; Hossam Afifi; Sofiane Boukli Hacene (GLOBECOM, 2018)

Hyperspectral Imagery Semantic Interpretation Based on Adaptive Constrained Band Selection and Knowledge Extraction Techniques. - Akrem Sellami; Mohamed Farah 001; Imed Riadh Farah; Basel Solaiman (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018)

Hyperspectral imagery classification based on semi-supervised 3-D deep neural network and adaptive band selection. - Akrem Sellami; Mohamed Farah 001; Imed Riadh Farah; Basel Solaiman (Expert Syst. Appl., 2019)

Bringing Deep Learning at the Edge of Information-Centric Internet of Things. - Hakima Khelifi; Senlin Luo; Boubakr Nour; Akrem Sellami; Hassine Moungla; Syed Hassan Ahmed; Mohsen Guizani (IEEE Commun. Lett., 2019)

Video semantic segmentation using deep multi-view representation learning. - Akrem Sellami; Salvatore Tabbone (ICPR, 2020)

Mapping individual differences in cortical architecture using multi-view representation learning. - Akrem Sellami; François-Xavier Dupé; Bastien Cagna; Hachem Kadri; Stéphane Ayache; Thierry Artières; Sylvain Takerkart (IJCNN, 2020)

Fused 3-D spectral-spatial deep neural networks and spectral clustering for hyperspectral image classification. - Akrem Sellami; Ali Ben Abbes; Vincent Barra; Imed Riadh Farah (Pattern Recognit. Lett., 2020)

BS-GAENets: Brain-Spatial Feature Learning Via a Graph Deep Autoencoder for Multi-modal Neuroimaging Analysis. - Refka Hanachi; Akrem Sellami; Imed Riadh Farah (VISIGRAPP (Revised Selected Papers), 2021)

EDNets: Deep Feature Learning for Document Image Classification Based on Multi-view Encoder-Decoder Neural Networks. - Akrem Sellami; Salvatore Tabbone (ICDAR (4), 2021)

Interpretation of Human Behavior from Multi-modal Brain MRI Images based on Graph Deep Neural Networks and Attention Mechanism. - Refka Hanachi; Akrem Sellami; Imed Riadh Farah (VISIGRAPP (4: VISAPP), 2021)

A deep learning approach based on morphological profiles for Hyperspectral Image unmixing. - Mariem Ayed; Refka Hanachi; Akrem Sellami; Imed Riadh Farah; Mauro Dalla Mura (ATSIP, 2022)

A Semi-supervised Graph Deep Neural Network for Automatic Protein Function Annotation. - Akrem Sellami; Bishnu Sarker; Salvatore Tabbone; Marie-Dominique Devignes; Sabeur Aridhi (IWBBIO (2), 2022)

Multi Spectral-Spatial Gabor Feature Fusion Based On End-To-End Deep Learning For Hyperspectral Image Classification. - Refka Hanachi; Akrem Sellami; Imed Riadh Farah; Mauro Dalla Mura (WHISPERS, 2022)

Deep neural networks-based relevant latent representation learning for hyperspectral image classification. - Akrem Sellami; Salvatore Tabbone (Pattern Recognit., 2022)

DNGAE: Deep Neighborhood Graph Autoencoder for Robust Blind Hyperspectral Unmixing. - Refka Hanachi; Akrem Sellami; Imed Riadh Farah; Mauro Dalla Mura (ICCCI, 2023)

Historical Document Image Segmentation Combining Deep Learning and Gabor Features. - Maroua Mehri; Akrem Sellami; Salvatore Tabbone (ICDAR (4), 2023)

SHCNet: A semi-supervised hypergraph convolutional networks based on relevant feature selection for hyperspectral image classification. - Akrem Sellami; Mohamed Farah 001; Mauro Dalla Mura (Pattern Recognit. Lett., 2023)

Geometric Deep Learning Techniques for Analyzing Brain 3D Meshes. - Mariem Ayad; Akrem Sellami; Imed Riadh Farah; Mauro Dalla Mura (ATSIP, 2024)

Advanced graph deep learning for High-dimensional image analysis: challenges and opportunities. - Refka Hanachi; Akrem Sellami; Imed Riadh Farah; Mauro Dalla Mura (ATSIP, 2024)

A Survey on Graph Deep Representation Learning for Facial Expression Recognition. - Théo Gueuret; Akrem Sellami; Chaabane Djeraba (CBMI, 2024)

Attention-driven multi-feature fusion for hyperspectral image classification via multi-criteria optimization and multi-view convolutional neural networks. - Sofiene Abidi; Akrem Sellami (Eng. Appl. Artif. Intell., 2024)

Graph feature fusion driven by deep autoencoder for advanced hyperspectral image unmixing. - Refka Hanachi; Akrem Sellami; Imed Riadh Farah; Mauro Dalla Mura (Knowl. Based Syst., 2024)

Multi-view graph representation learning for hyperspectral image classification with spectral-spatial graph neural networks. - Refka Hanachi; Akrem Sellami; Imed Riadh Farah; Mauro Dalla Mura (Neural Comput. Appl., 2024)