Optimised feature selection-driven convolutional neural network using gray level co-occurrence matrix for detection of cervical cancer

Optimised feature selection-driven convolutional neural network using gray level co-occurrence matrix for detection of cervical cancer

Cervical cancer is one of the most dangerous and widespread illnesses afflicting women throughout the globe, particularly in East Africa and South Asia. In industrialised nations, the incidence of cervical cancer has consistently decreased over the past few decades. However, in developing countries,...

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Bibliographic Details
Main Authors: Sudhakar K., Saravanan D., Hariharan G., Sanaj M. S., Kumar Santosh, Shaik Maznu, Gonzales Jose Luis Arias, Aurangzeb Khursheed
Format: Article
Language:English
Published: De Gruyter 2023-11-01
Series:Open Life Sciences
Subjects:
cervical cancer detection
convolutional neural network
accuracy
gray level co-occurrence matrix
feature selection
pep test images
Online Access:https://doi.org/10.1515/biol-2022-0770

Internet

https://doi.org/10.1515/biol-2022-0770

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