Souleyman Chaib

Orcid: 0000-0002-5911-3128

According to our database1, Souleyman Chaib authored at least 13 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

Online presence:

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Bibliography

2023
CoSP: co-selection pick for a global explainability of black box machine learning models.
World Wide Web (WWW), November, 2023

VeSoNet: Traffic-Aware Content Caching for Vehicular Social Networks Using Deep Reinforcement Learning.
IEEE Trans. Intell. Transp. Syst., August, 2023

2022
On the Co-Selection of Vision Transformer Features and Images for Very High-Resolution Image Scene Classification.
Remote. Sens., 2022

Towards a Co-selection Approach for a Global Explainability of Black Box Machine Learning Models.
Proceedings of the Web Information Systems Engineering - WISE 2022, 2022

2021
Dual link distributed source coding scheme for the transmission of satellite hyperspectral imagery.
J. Vis. Commun. Image Represent., 2021

A Hybrid Model Combining Learning Distance Metric and DAG Support Vector Machine for Multimodal Biometric Recognition.
IEEE Access, 2021

2019
Transfer Learning for Changes Detection in Optical Remote Sensing Imagery.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Very High Resolution Image Scene Classification with Capsule Network.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Improvememt of multi-temporal vegetation modeling using hybrid deep neural networks of multispectral remote sensing images.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Very High Resolution Image Scene Classification with Semantic Fisher Vectors.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Deep Feature Fusion for VHR Remote Sensing Scene Classification.
IEEE Trans. Geosci. Remote. Sens., 2017

2016
An Informative Feature Selection Method Based on Sparse PCA for VHR Scene Classification.
IEEE Geosci. Remote. Sens. Lett., 2016

A VHR scene classification method integrating sparse PCA and saliency computing.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016


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