Work

Implementation of the CNN Algorithm for Classification of Electric Meter Recording Images

Year: 2024

Type: article

Abstract: Electricity is a basic human need in carrying out every activity. Electricity usage can be measured using a KWH meter. In Indonesia, electricity customers are divided into two, namely Prepaid and Postpaid. Postpaid electricity customers need to record the numbers written on the KWH meter to find out the rupiah electricity bill that must be charged. In the implementation of recording these numbers, it is not uncommon to encounter obstacles such as a locked customer's fence and so on, so the meter reading results must be re-validated. This study aims to validate the meter record images which are classified into three classes using the Convolutional Neural Network (CNN) algorithm with the Resnet34 architecture. In this study, the highest accuracy level for the Resnet34 architecture was obtained, with an accuracy rate of 97.50%.

Source: International Journal of Scientific Research in Computer Science Engineering and Information Technology

DOI: 10.32628/cseit2410417

Authors: Harni Kusniyati, Raka Yusuf, Nuryasin

Institutions: Mercu Buana University, Syarif Hidayatullah State Islamic University Jakarta

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4404507200

FWCI:

Cites: 4

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Related to: 10