Get started
Author

Refka Hanachi

ORCID: 0000-0001-8244-3574
Observed ORCID: 0000-0001-8244-3574
OpenAlex ID: A5084022253
Multi-view graph representation learning for hyperspectral image classification with spectral–spatial graph neural networks
2023 · Refka Hanachi, Akrem Sellami, et al. · Neural Computing and Applications · 26
Semi-supervised Classification of Hyperspectral Image through Deep Encoder-Decoder and Graph Neural Networks
2021 · Refka Hanachi, Akrem Sellami, et al. · International Congress of Advanced Technology and Engineering (ICOTEN) · 15
Graph feature fusion driven by deep autoencoder for advanced hyperspectral image unmixing
2024 · Refka Hanachi, Akrem Sellami, et al. · Knowledge-Based Systems · 12
Interpretation of Human Behavior from Multi-modal Brain MRI Images based on Graph Deep Neural Networks and Attention Mechanism
2021 · Refka Hanachi, Akrem Sellami, et al. · International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) · 10
A deep learning approach based on morphological profiles for Hyperspectral Image unmixing
2022 · Mariem Ayed, Refka Hanachi, et al. · International Conference on Advanced Technologies for Signal and Image Processing · 7
BS-GAENets: Brain-Spatial Feature Learning Via a Graph Deep Autoencoder for Multi-modal Neuroimaging Analysis
2023 · Refka Hanachi, Akrem Sellami, et al. · Communications in computer and information science · 2
Multi Spectral-Spatial Gabor Feature Fusion Based On End-To-End Deep Learning For Hyperspectral Image Classification
2022 · Refka Hanachi, Akrem Sellami, et al. · Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing · 2
DNGAE: Deep Neighborhood Graph Autoencoder for Robust Blind Hyperspectral Unmixing
2023 · Refka Hanachi, Akrem Sellami, et al. · Lecture notes in computer science · 1
Advanced graph deep learning for High-dimensional image analysis: challenges and opportunities
2024 · Refka Hanachi, Akrem Sellami, et al. · International Conference on Advanced Technologies for Signal and Image Processing
Works count: 9
Citation count: 75
H-index: 5
I10-index: 4
Year
Topic
Type