Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Technomedia Journal
Nadia Azahro Choirunisa
Politeknik Elektronika Negeri Surabaya
Computer Science & IT Languange, Linguistic, Communication & Media

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Deteksi Ras Kucing Menggunakan Compound Model Scaling Convolutional Neural Network Nadia Azahro Choirunisa; Tita Karlita; Rengga Asmara
Technomedia Journal Vol 6 No 2 Februari (2022): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1114.419 KB) | DOI: 10.33050/tmj.v6i2.1704

Abstract

Cat is one of a popular animals in the world. Number of cat breeds in the world only about 1%, so most are dominated by cats mixed or domestic cat. Nevertheless, there are so many different types of cat breeds in the world, that it is sometimes difficult to identify them. Therefore, we need a system that can recognize the types of cat breeds. One technique of deep learning that may apprehend and hit upon gadgets in a photograph is Convolutional Neural Network (CNN). CNN functionality is alleged because the nice technique in phrases of item detection and item recognition. The author used 9 different types of cat breeds containing 2700 images. The EfficientNet-B0 architecture is used on the system. The most optimal model has earned the accuracy of 95%. Keywords : Deep Learning, Convolutional Neural Network (CNN), Cat breeds, EfficientNet-B0.
Co-Authors Rengga Asmara Tita Karlita