The Utilization of Padding Scheme on Convolutional Neural Network for Cervical Cell Images Classification

Toto Haryanto,Imas Sukaesih Sitanggang,Riries Rulaningtyas,Muhammad Ashyar Agmalaro

doi:10.1109/cenim51130.2020.9297895

The Utilization of Padding Scheme on Convolutional Neural Network for Cervical Cell Images Classification

Toto Haryanto, Imas Sukaesih Sitanggang + Show 2 more

https://doi.org/10.1109/cenim51130.2020.9297895

Copy DOI

Publication Date: Nov 17, 2020

Citations: 23

Affiliation: Bogor Agricultural University, Airlangga University

#Convolutional Neural Network Algorithm #AlexNet Architecture + Show 8 more

Abstract
Full-Text PDF
Similar Papers

Abstract

Cervical cancer identification through pap-smear images analysis is a challenge for medicians, especially in distinguishing cells, between the normal and abnormal one. This study aims to create the classification model of Cervical Cell Images using the Convolutional Neural Network (CNN) algorithm. The dataset used is the image dataset SIPaKMeD. The CNN algorithm was implemented using the AlexNet architecture with and non-padding scheme. Padding is included in the experiments by adding the pixel 0 on the original images to improve the accuracy of the model. The experimental results show that using the utilization padding scheme on the AlexNet architecture can increase the accuracy of the model slightly significantly from 84.88% to 87.32%.

Full Text