Indonesian Traditional Cake Classification Using Convolutional Neural Networks

DOI

10.2991/assehr.k.220301.153How to use a DOI?

Keywords

convolutional neural networks; transfer learning; mobilenetv2; Indonesian traditional cake

Abstract

In Indonesia, there are many types of cakes that are categorized as traditional snacks. Refer to the Kamus Besar Bahasa Indonesia; snacks are defined as foods that are peddled or mean bites. Snacks are classified based on how they are made, and some are based on the taste of the snacks. Traditional snacks are a part of Nusantara culture that is mandatory for those born and live in Indonesia to preserve them. But in reality, many people tend to consume and know more about modern snacks than traditional ones. In fact, not many people have even tried traditional snacks or even made their own at home. This application was developed to help people distinguish and recognize the various kinds of cakes on the market. With convolutional neural networks technology in machine learning, people can use image classification presented through mobile applications with accuracy above 90% for Indonesian traditional cake recognition.

Copyright

© 2022 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Tita Karlita
AU  - Bimo Prasetyo Afif
AU  - Ira Prasetyaningrum
PY  - 2022
DA  - 2022/03/04
TI  - Indonesian Traditional Cake Classification Using Convolutional Neural Networks
BT  - Proceedings of the International Conference on Applied Science and Technology on Social Science 2021 (iCAST-SS 2021)
PB  - Atlantis Press
SP  - 924
EP  - 929
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220301.153
DO  - 10.2991/assehr.k.220301.153
ID  - Karlita2022
ER  -