Grey Blight Disease Detection on Tea Leaves Using Improved Deep Convolutional Neural Network

We proposed a novel deep convolutional neural network (DCNN) using inverted residuals and linear bottleneck layers for diagnosing grey blight disease on tea leaves. The proposed DCNN consists of three bottleneck blocks, two pairs of convolutional (Conv) layers, and three dense layers. The bottleneck...

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Detalles Bibliográficos
Autores principales: Pandian, J. Arun, Nisha, Sam Nirmala, Kanchanadevi, K., Pandey, Abhay K., Rima, Samira Kabir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9873464/
https://www.ncbi.nlm.nih.gov/pubmed/36703994
http://dx.doi.org/10.1155/2023/7876302

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9873464/
https://www.ncbi.nlm.nih.gov/pubmed/36703994
http://dx.doi.org/10.1155/2023/7876302

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