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BeeNet: Reconstructing Flower Shapes from Electric Fields using Deep Learning

Year: 2025

Type: article

Abstract: Training data for a deep learning model to reconstructing flower shapes from electric fields. Link to paper: https://doi.org/10.48550/arXiv.2508.11724 Link to github: https://github.com/turleyjm/BeeNet

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.16879469

Authors: Turley, Jake, Palmer, Ryan, Chenchiah, Isaac, Robert, Daniel

Institutions: National University of Singapore, University of Bristol

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6930836403

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