TIA-YOLOv5: An improved YOLOv5 network for real-time detection of crop and weed in the field

INTRODUCTION: Development of weed and crop detection algorithms provides theoretical support for weed control and becomes an effective tool for the site-specific weed management. For weed and crop object detection tasks in the field, there is often a large difference between the number of weed and c...

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Detalles Bibliográficos
Autores principales: Wang, Aichen, Peng, Tao, Cao, Huadong, Xu, Yifei, Wei, Xinhua, Cui, Bingbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Plant Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815699/
https://www.ncbi.nlm.nih.gov/pubmed/36618638
http://dx.doi.org/10.3389/fpls.2022.1091655

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815699/
https://www.ncbi.nlm.nih.gov/pubmed/36618638
http://dx.doi.org/10.3389/fpls.2022.1091655

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