Five-Class Classification of Cervical Pap Smear Images: A Study of CNN-Error-Correcting SVM Models

OBJECTIVES: Different complex strategies of fusing handcrafted descriptors and features from convolutional neural network (CNN) models have been studied, mainly for two-class Papanicolaou (Pap) smear image classification. This paper explores a simplified system using combined binary coding for a fiv...

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Detalles Bibliográficos
Autores principales: Huong, Audrey K. C., Tay, Kim Gaik, Ngu, Xavier T. I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654336/
https://www.ncbi.nlm.nih.gov/pubmed/34788910
http://dx.doi.org/10.4258/hir.2021.27.4.298

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654336/
https://www.ncbi.nlm.nih.gov/pubmed/34788910
http://dx.doi.org/10.4258/hir.2021.27.4.298

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