Crop Identification Using Deep Learning on LUCAS Crop Cover Photos

Massive and high-quality in situ data are essential for Earth-observation-based agricultural monitoring. However, field surveying requires considerable organizational effort and money. Using computer vision to recognize crop types on geo-tagged photos could be a game changer allowing for the provisi...

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Detalles Bibliográficos
Autores principales: Yordanov, Momchil, d’Andrimont, Raphaël, Martinez-Sanchez, Laura, Lemoine, Guido, Fasbender, Dominique, van der Velde, Marijn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383911/
https://www.ncbi.nlm.nih.gov/pubmed/37514593
http://dx.doi.org/10.3390/s23146298

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383911/
https://www.ncbi.nlm.nih.gov/pubmed/37514593
http://dx.doi.org/10.3390/s23146298

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