Abstract

Nails are one part of the fingers and toes, by observing the shape and the condition of the nails, health expert can find out information about a person’s health. However, this sometimes not realized and ignored by society, even though many diseases that can be seen through the condition of the nails and the shape of the nails are one of the systemic diseases. This research was conducted to detect abnormalities in the nail based on digital images. The detected abnormalities are terry’s nails in the hand which can represent systemic diseases, while the method used is the Convolutional Neural Network (CNN) method. This research uses Tensorflow Inception-V3 architecture model with the transfer learning method where the results of the experiments that have been done are obtained with 95.24% accuracy.

Details

Title
Application of Transfer Learning Using Convolutional Neural Network Method for Early Detection of Terry’s Nail
Author
Yani, Muhamad 1 ; S, Si, MT Budhi Irawan 2 ; ST, MT Casi Setiningsih 3 

 Student, Faculty of Electrical Engineering, Telkom University, Bandung, Indonesia. 
 Lecturer, Faculty of Electrical Engineering, Telkom University, Bandung, Indonesia. 
 Lecturer Faculty of Electrical Engineering, Telkom University, Bandung, Indonesia. 
Publication year
2019
Publication date
May 2019
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2566105078
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.