Akrem Sellami
Orcid: 0000-0003-1534-1687
According to our database1,
Akrem Sellami
authored at least 28 papers
between 2014 and 2024.
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Bibliography
2024
Multi-view graph representation learning for hyperspectral image classification with spectral-spatial graph neural networks.
Neural Comput. Appl., 2024
Graph feature fusion driven by deep autoencoder for advanced hyperspectral image unmixing.
Knowl. Based Syst., 2024
Attention-driven multi-feature fusion for hyperspectral image classification via multi-criteria optimization and multi-view convolutional neural networks.
Eng. Appl. Artif. Intell., 2024
CoRR, 2024
Advanced graph deep learning for High-dimensional image analysis: challenges and opportunities.
Proceedings of the 7th IEEE International Conference on Advanced Technologies, 2024
Proceedings of the 7th IEEE International Conference on Advanced Technologies, 2024
2023
SHCNet: A semi-supervised hypergraph convolutional networks based on relevant feature selection for hyperspectral image classification.
Pattern Recognit. Lett., January, 2023
Proceedings of the Document Analysis and Recognition - ICDAR 2023, 2023
Proceedings of the Computational Collective Intelligence - 15th International Conference, 2023
2022
Deep neural networks-based relevant latent representation learning for hyperspectral image classification.
Pattern Recognit., 2022
Multi Spectral-Spatial Gabor Feature Fusion Based On End-To-End Deep Learning For Hyperspectral Image Classification.
Proceedings of the 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2022
A Semi-supervised Graph Deep Neural Network for Automatic Protein Function Annotation.
Proceedings of the Bioinformatics and Biomedical Engineering, 2022
A deep learning approach based on morphological profiles for Hyperspectral Image unmixing.
Proceedings of the 6th International Conference on Advanced Technologies for Signal and Image Processing, 2022
2021
Interpretation of Human Behavior from Multi-modal Brain MRI Images based on Graph Deep Neural Networks and Attention Mechanism.
Proceedings of the 16th International Joint Conference on Computer Vision, 2021
EDNets: Deep Feature Learning for Document Image Classification Based on Multi-view Encoder-Decoder Neural Networks.
Proceedings of the 16th International Conference on Document Analysis and Recognition, 2021
BS-GAENets: Brain-Spatial Feature Learning Via a Graph Deep Autoencoder for Multi-modal Neuroimaging Analysis.
Proceedings of the Computer Vision, Imaging and Computer Graphics Theory and Applications, 2021
2020
Fused 3-D spectral-spatial deep neural networks and spectral clustering for hyperspectral image classification.
Pattern Recognit. Lett., 2020
Mapping individual differences in cortical architecture using multi-view representation learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 25th International Conference on Pattern Recognition, 2020
2019
IEEE Commun. Lett., 2019
Hyperspectral imagery classification based on semi-supervised 3-D deep neural network and adaptive band selection.
Expert Syst. Appl., 2019
2018
Hyperspectral Imagery Semantic Interpretation Based on Adaptive Constrained Band Selection and Knowledge Extraction Techniques.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018
Proceedings of the IEEE Global Communications Conference, 2018
An Optimized Proactive Caching Scheme Based on Mobility Prediction for Vehicular Networks.
Proceedings of the IEEE Global Communications Conference, 2018
Comparative study of dimensionality reduction methods for remote sensing images interpretation.
Proceedings of the 4th International Conference on Advanced Technologies for Signal and Image Processing, 2018
An adaptive semantic dimensionality reduction approach for hyperspectral imagery classification.
Proceedings of the 4th International Conference on Advanced Technologies for Signal and Image Processing, 2018
2017
Interprétation sémantique d'images hyperspectrales basée sur la réduction adaptative de dimensionnalité. (Semantic interpretation of hyperspectral images based on the adaptative reduction of dimensionality).
PhD thesis, 2017
2014
Interpretation of hyperspectral imagery based on hybrid dimensionality reduction methods.
Proceedings of the International Image Processing, 2014