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All Journal Mobile and Forensics Signal and Image Processing Letters
Adhi Prahara, Adhi
Universitas Ahmad Dahlan
Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Library & Information Science Neuroscience

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Journal : Mobile and Forensics

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Classification of Tiles using Convolutional Neural Network Ramadayanti, Susanti Aulia; Prahara, Adhi
Mobile and Forensics Vol. 3 No. 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v3i2.5643

Abstract

Tiles are one of the building materials with various types that can make a residence more elegant, attractive, and colorful. However, not all people know about the types of tiles and their advantages. Therefore, a Convolutional Neural Networks (CNN) based method is proposed to make it easier for people to accurately recognize tiles based on their types and know their advantages. The purpose of this paper is to classify the types of tiles using CNN which is based on VGG16 model. The proposed method classifies tiles into 6 classes, namely granite, limestone, marble, motifs, mosaics, and terrazzo. This research uses 186 training data, 96 validation data and 60 test data with image resolution of 224x224. Based on the experiments, the training process produces 100% of training accuracy and 94% of validation accuracy. The testing process achieves 98.33% accuracy which can be concluded that the proposed CNN model able to classify the types of tiles well.
Co-Authors A.A. Ketut Agung Cahyawan W Anwar, Kaspul Arif Budi Setiawan Fatkhannudin, Muhammad Noor Fatkhannudin, Muhammad Noor Laelatul Azizah, Laelatul Ramadayanti, Susanti Aulia