Weakly Supervised Collaborative Learning for Airborne Pollen Segmentation and Classification from SEM Images

Existing pollen identification methods heavily rely on the scale and quality of pollen images. However, there are many impurities in real-world SEM images that should be considered. This paper proposes a collaborative learning method to jointly improve the performance of pollen segmentation and clas...

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Detalles Bibliográficos
Autores principales: Li, Jianqiang, Xu, Qinlan, Cheng, Wenxiu, Zhao, Linna, Liu, Suqin, Gao, Zhengkai, Xu, Xi, Ye, Caihua, You, Huanling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9867018/
https://www.ncbi.nlm.nih.gov/pubmed/36676197
http://dx.doi.org/10.3390/life13010247

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9867018/
https://www.ncbi.nlm.nih.gov/pubmed/36676197
http://dx.doi.org/10.3390/life13010247

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