MARBLE CLASSIFICATION USING DEEP NEURAL NETWORKS

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

European Journal of Technique
Volume:10 Issue:1
MARBLE CLASSIFICATION USING DEEP NEURAL NETWORKS

MARBLE CLASSIFICATION USING DEEP NEURAL NETWORKS

Authors : Murat CANAYAZ, Fatih ULUDAĞ

Pages : 52-63

Doi:10.36222/ejt.671527

View : 17 | Download : 11

Publication Date : 2020-06-01

Article Type : Research Paper

Abstract :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.
Keywords : Marble Classification, Deep Neural Networks, VGG16, ResNet

ORIGINAL ARTICLE URL

VIEW PAPER (PDF)

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.