MARBLE CLASSIFICATION USING DEEP NEURAL NETWORKS

Yıl 2020, Cilt: 10 Sayı: 1, 52 - 63, 01.06.2020

Murat Canayaz , Fatih Uludağ

https://doi.org/10.36222/ejt.671527

Cited By: 4

Öz

Deep learning, which has been described as the processing and interpretation of data, is now widely used. In this study, deep neural networks are used for the classification of marbles which can be used in the industry. For this purpose most used marbles images were obtained from companies in Turkey and 28-class dataset was created. Then VGG16, ResNet and LeNet models were trained on this dataset. Data augmentation was performed to have class balance. To evaluate the models performance accuracy metric is used. In the VGG16 model, fine tunning was applied and %97 accuracy was achieved. In experimental studies, models were trained with different parameter settings. The performances of the models are given comparatively. The fact that both new dataset and deep neural networks are used for the first time in marble classification are among the positive aspects of this study. It is planned to integrate the models produced in the future studies into mobile based expert systems.

Anahtar Kelimeler

Marble Classification, Deep Neural Networks, VGG16, ResNet

Proje Numarası

FBA-2018-6915

Kaynakça

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