11 citations as recorded by crossref.

1. Using Machine Learning for the Calibration of Airborne Particulate Sensors L. Wijeratne et al. 10.3390/s20010099
2. Autonomous Learning of New Environments with a Robotic Team Employing Hyper-Spectral Remote Sensing, Comprehensive In-Situ Sensing and Machine Learning D. Lary et al. 10.3390/s21062240
3. Using deep learning to extend the range of air pollution monitoring and forecasting P. Hähnel et al. 10.1016/j.jcp.2020.109278
4. Machine learning in geosciences and remote sensing D. Lary et al. 10.1016/j.gsf.2015.07.003
5. A Fortran-Keras Deep Learning Bridge for Scientific Computing J. Ott et al. 10.1155/2020/8888811
6. Forecasting closures on shellfish farms using machine learning F. O’Donncha et al. 10.1007/s10499-024-01438-y
7. A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales F. O'Donncha et al. 10.1016/j.ecoinf.2022.101687
8. Multi-annual changes of NOx emissions in megacity regions: nonlinear trend analysis of satellite measurement based estimates I. Konovalov et al. 10.5194/acp-10-8481-2010
9. An intelligent clustering method for devising the geochemical fingerprint of underground aquifers A. Di Roma et al. 10.1016/j.heliyon.2021.e07017
10. Ozone ensemble forecast with machine learning algorithms V. Mallet et al. 10.1029/2008JD009978
11. Using Machine Learning for the Calibration of Airborne Particulate Sensors L. Wijeratne et al. 10.3390/s20010099