Embracing limited and imperfect training datasets: opportunities and challenges in plant disease recognition using deep learning

Recent advancements in deep learning have brought significant improvements to plant disease recognition. However, achieving satisfactory performance often requires high-quality training datasets, which are challenging and expensive to collect. Consequently, the practical application of current deep...

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Detalles Bibliográficos
Autores principales: Xu, Mingle, Kim, Hyongsuk, Yang, Jucheng, Fuentes, Alvaro, Meng, Yao, Yoon, Sook, Kim, Taehyun, Park, Dong Sun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Plant Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557492/
https://www.ncbi.nlm.nih.gov/pubmed/37810377
http://dx.doi.org/10.3389/fpls.2023.1225409

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557492/
https://www.ncbi.nlm.nih.gov/pubmed/37810377
http://dx.doi.org/10.3389/fpls.2023.1225409

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