Correa-Luna, M., Gargiulo, J., Beale, P., Deane, D., Leonard, J., Hack, J., Geldof, Z., Wilson, C., & Garcia, S. (2024). Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-68094-3

CORREA-LUNA, Martin, GARGIULO, Juan, BEALE, Peter, DEANE, David, LEONARD, Jacob, HACK, Josh, GELDOF, Zac, WILSON, Chloe und GARCIA, Sergio, 2024. Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing. Scientific Reports. 1 Dezember 2024. Vol. 14, no. 1, . DOI 10.1038/s41598-024-68094-3.

Correa-Luna, M., J. Gargiulo, P. Beale, D. Deane, J. Leonard, J. Hack, Z. Geldof, C. Wilson, und S. Garcia. „Accounting for Minimum Data Required to Train a Machine Learning Model to Accurately Monitor Australian Dairy Pastures Using Remote Sensing“. Scientific Reports, Bd. 14, Nr. 1, Dezember 2024, https://doi.org/10.1038/s41598-024-68094-3.

Correa-Luna, Martin/Gargiulo, Juan/Beale, Peter/Deane, David/Leonard, Jacob/Hack, Josh u. a.: Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing, Scientific Reports 2024,

Correa-Luna, M., Gargiulo, J., Beale, P., Deane, D., Leonard, J., Hack, J., Geldof, Z., Wilson, C. und Garcia, S. (2024), „Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing“, Scientific Reports, Vol. 14 No. 1, verfügbar unter:https://doi.org/10.1038/s41598-024-68094-3.