Classification of Minerals Using Machine Learning Methods
Küçük Resim Yok
Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Minerals are the structures formed by the combination of one or more elements as a result of geological process. The discipline which examines all aspects of minerals is called mineralogy. In mineralogy science, the definition and classification of minerals are made by taking into account many properties such as physical and chemical properties, internal crystal structures and optical properties. The classification of minerals has an important place in many engineering fields and such as geology, mining, geophysics, environment and in many fields such as mineral exploration, gemology, prospecting, ore processing. Both in the field environment and then in the laboratory environment, determination of all the properties of the mineral found in the field, is quite a long process. In addition, the researcher should have a good experience in the identification and classification process. In order to shorten this process in this study, it is aimed to classify minerals taken directly from the field and photographed, with AlexNet one of the convolutional neural network (CNN) architectures. In this study, 1491 images were used in 8 classes.
Açıklama
28th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORK
Anahtar Kelimeler
Deep Learning, Mineral, Cnn, Alexnet
Kaynak
2020 28Th Signal Processing and Communications Applications Conference (Siu)
WoS Q Değeri
N/A
