Improvement of Satellite Image Classification Using Attention-Based Vision Transformer

Nawel Slimani, Imen Jdey, Monji Kherallah

2024

Abstract

This study introduces a transformative approach to satellite image classification using the Vision Transformer (ViT) model, a revolutionary deep learning method. Unlike conventional methods, ViT divides images into patches and employs self-attention mechanisms to capture intricate spatial dependencies, enabling the discernment of nuanced patterns at the patch level. This key innovation results in remarkable classification accuracy, surpassing 98% for SAT4 and SAT6 datasets. The study’s findings hold substantial promise for diverse applications, including urban planning, agriculture, disaster response, and environmental conservation. By providing a nuanced understanding of ViT’s impact on satellite imagery analysis, this work not only contributes insights into ViT’s architecture and training process but also establishes a robust foundation for advancing the field and promoting sustainable resource management through informed decision-making.

Paper Citation

in Harvard Style

Slimani N., Jdey I. and Kherallah M. (2024). Improvement of Satellite Image Classification Using Attention-Based Vision Transformer. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 80-87. DOI: 10.5220/0012298400003636

in Bibtex Style

@conference{icaart24,
author={Nawel Slimani and Imen Jdey and Monji Kherallah},
title={Improvement of Satellite Image Classification Using Attention-Based Vision Transformer},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={80-87},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012298400003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Improvement of Satellite Image Classification Using Attention-Based Vision Transformer
SN - 978-989-758-680-4
AU - Slimani N.
AU - Jdey I.
AU - Kherallah M.
PY - 2024
SP - 80
EP - 87
DO - 10.5220/0012298400003636
PB - SciTePress