A new model based on improved VGG16 for corn weed identification

Weeds remain one of the most important factors affecting the yield and quality of corn in modern agricultural production. To use deep convolutional neural networks to accurately, efficiently, and losslessly identify weeds in corn fields, a new corn weed identification model, SE-VGG16, is proposed. T...

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Detalles Bibliográficos
Autores principales: Yang, Le, Xu, Shuang, Yu, XiaoYun, Long, HuiBin, Zhang, HuanHuan, Zhu, YingWen
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/PMC10361060/
https://www.ncbi.nlm.nih.gov/pubmed/37484459
http://dx.doi.org/10.3389/fpls.2023.1205151

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10361060/
https://www.ncbi.nlm.nih.gov/pubmed/37484459
http://dx.doi.org/10.3389/fpls.2023.1205151

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