A deep learning framework to discern and count microscopic nematode eggs

In order to identify and control the menace of destructive pests via microscopic image-based identification state-of-the art deep learning architecture is demonstrated on the parasitic worm, the soybean cyst nematode (SCN), Heterodera glycines. Soybean yield loss is negatively correlated with the de...

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Detalles Bibliográficos
Autores principales: Akintayo, Adedotun, Tylka, Gregory L., Singh, Asheesh K., Ganapathysubramanian, Baskar, Singh, Arti, Sarkar, Soumik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6002363/
https://www.ncbi.nlm.nih.gov/pubmed/29904135
http://dx.doi.org/10.1038/s41598-018-27272-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6002363/
https://www.ncbi.nlm.nih.gov/pubmed/29904135
http://dx.doi.org/10.1038/s41598-018-27272-w

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