Image Classification of Graphene Oxide Thin Films’ Sheet Resistance using a Convolution Neural Network

Image Classification of Graphene Oxide Thin Films’ Sheet Resistance using a Convolution Neural Network

This study focuses on developing a CNN model, VGG-16, to classify microscopy images of graphene oxide thin films produced by two machines; Atomizer 2 and Atomizer 3 based on the sheet resistance values. The methodology begins with preparing microscopic images of graphene oxide thin films dataset. Th...

詳細記述

書誌詳細
出版年:2024 IEEE 7th International Conference on Electrical, Electronics, and System Engineering: Dissemination and Advancement of Engineering Education using Artificial Intelligence, ICEESE 2024
第一著者: Yusri M.W.B.; Masrie M.; Badaruddin S.A.M.; Burham N.; Janin Z.; Saad H.
フォーマット: Conference paper
言語:English
出版事項: Institute of Electrical and Electronics Engineers Inc. 2024
オンライン･アクセス:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85217396453&doi=10.1109%2fICEESE62315.2024.10828545&partnerID=40&md5=f208c37a81cd53bc6fbb06b3ce32aa28

インターネット

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85217396453&doi=10.1109%2fICEESE62315.2024.10828545&partnerID=40&md5=f208c37a81cd53bc6fbb06b3ce32aa28

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