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Cited by in F6Publishing
For: Pinto VA, Keesee AM, Coughlan M, Mukundan R, Johnson JW, Ngwira CM, Connor HK. Revisiting the Ground Magnetic Field Perturbations Challenge: A Machine Learning Perspective. Front Astron Space Sci 2022;9:869740. [DOI: 10.3389/fspas.2022.869740] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Siddique T, Mahmud MS. Ensemble deep learning models for prediction and uncertainty quantification of ground magnetic perturbation. Front Astron Space Sci 2022;9. [DOI: 10.3389/fspas.2022.1031407] [Reference Citation Analysis]
2 Siddique T, Mahmud MS. Real-Time Machine Learning Enabled Low-Cost Magnetometer System. 2022 IEEE Sensors 2022. [DOI: 10.1109/sensors52175.2022.9967170] [Reference Citation Analysis]
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