Публікація:
Neural Networks As A Tool For Pattern Recognition of Fasteners

dc.contributor.authorAl-Sharo Yasser Mohammad
dc.contributor.authorAbu-Jassar Amer Tahseen
dc.contributor.authorSotnik, S.
dc.contributor.authorLyashenko, V.
dc.date.accessioned2021-10-09T10:58:40Z
dc.date.available2021-10-09T10:58:40Z
dc.date.issued2021
dc.description.abstractThe work is devoted to the study of pattern recognition features of industrial parts in individual fasteners' forms. The main types of neural network architectures and their features are considered. Neural networks are classified into separate categories for ease of perception and analysis. An approach to recognition of hardware products such as fasteners using neural network, which is implemented in Python using Keras machine learning library, is proposed. The main generators are described: for training data, testing, and validation. Codes fragments of corresponding programs for implementation of the proposed approach to pattern recognition of fasteners are presenteduk_UA
dc.identifier.citationAl-Sharo Y. M., Abu-Jassar A. T., Sotnik S., Lyashenko V. Neural Networks As A Tool For Pattern Recognition of Fasteners // International Journal of Engineering Trends and Technology. – 2021. –69(10). – pp. 151-160.uk_UA
dc.identifier.issn2231-5381
dc.identifier.urihttps://openarchive.nure.ua/handle/document/17864
dc.language.isoenuk_UA
dc.publisherSeventh Sense Research Groupuk_UA
dc.subjectNeural Networksuk_UA
dc.subjectrecognitionuk_UA
dc.titleNeural Networks As A Tool For Pattern Recognition of Fastenersuk_UA
dc.typeArticleuk_UA
dspace.entity.typePublication

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