Leveraging feature communication in federated learning for remote sensing image classification
Fuente:
arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866911884476678144 |
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| author | Duong, Anh-Kiet Lê, Hoàng-Ân Pham, Minh-Tan |
| author_facet | Duong, Anh-Kiet Lê, Hoàng-Ân Pham, Minh-Tan |
| contents | In the realm of Federated Learning (FL) applied to remote sensing image classification, this study introduces and assesses several innovative communication strategies. Our exploration includes feature-centric communication, pseudo-weight amalgamation, and a combined method utilizing both weights and features. Experiments conducted on two public scene classification datasets unveil the effectiveness of these strategies, showcasing accelerated convergence, heightened privacy, and reduced network information exchange. This research provides valuable insights into the implications of feature-centric communication in FL, offering potential applications tailored for remote sensing scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_13575 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Leveraging feature communication in federated learning for remote sensing image classification Duong, Anh-Kiet Lê, Hoàng-Ân Pham, Minh-Tan Computer Vision and Pattern Recognition In the realm of Federated Learning (FL) applied to remote sensing image classification, this study introduces and assesses several innovative communication strategies. Our exploration includes feature-centric communication, pseudo-weight amalgamation, and a combined method utilizing both weights and features. Experiments conducted on two public scene classification datasets unveil the effectiveness of these strategies, showcasing accelerated convergence, heightened privacy, and reduced network information exchange. This research provides valuable insights into the implications of feature-centric communication in FL, offering potential applications tailored for remote sensing scenarios. |
| title | Leveraging feature communication in federated learning for remote sensing image classification |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2403.13575 |