Design of Convolutional Neural Networks Model for Fine-Grained Classification of Cervical Cells
Main Article Content
Abstract
One of the most prevalent cancers in the world and one of the most harmful to human life is cervical cancer (CC). This procedure was created to increase the diagnostic accuracy of CC in such dataset pictures in order to better detect and forecast illness. Therefore, we attempted to demonstrate a convolution neural network-based classification framework for CC that is intelligent and effective and has a comparatively basic architecture in comparison to others. Additionally, we offered a simple and useful technique for CC classification from cytological pictures using effective feature extraction or accurate cell image segmentation effort. The outcomes of automatic cell detection are contrasted with those of other cutting-edge cell detection methods as well as hand annotation of the underlying data. Many of the procedures for cell detection and categorization are still being worked on. This procedure's primary goals are to pinpoint the cell area and increase segmentation precision. With an F1 score of 0.96, the suggested approach has the highest cell detection accuracy.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
