Quantum Transfer Learning for Real-World, Small, and High-Dimensional Remotely Sensed Datasets
Quantum machine learning (QML) models promise to have some computational (or quantum) advantage for classifying supervised datasets (e.g., satellite images) over some conventional deep learning (DL) techniques due to their expressive power via their local effective dimension. There are, however, two...
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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
IEEE
2023-01-01
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| Col·lecció: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Matèries: | |
| Accés en línia: | https://ieeexplore.ieee.org/document/10253962/ |
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