Weed Growth Stage Estimator Using Deep Convolutional Neural Networks

This study outlines a new method of automatically estimating weed species and growth stages (from cotyledon until eight leaves are visible) of in situ images covering 18 weed species or families. Images of weeds growing within a variety of crops were gathered across variable environmental conditions...

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Detalles Bibliográficos
Autores principales: Teimouri, Nima, Dyrmann, Mads, Nielsen, Per Rydahl, Mathiassen, Solvejg Kopp, Somerville, Gayle J., Jørgensen, Rasmus Nyholm
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5981438/
https://www.ncbi.nlm.nih.gov/pubmed/29772666
http://dx.doi.org/10.3390/s18051580

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5981438/
https://www.ncbi.nlm.nih.gov/pubmed/29772666
http://dx.doi.org/10.3390/s18051580

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