Neural Networks As A Tool For Pattern Recognition of Fasteners

Al-Sharo Yasser Mohammad; Abu-Jassar Amer Tahseen; Sotnik, S.; Lyashenko, V.

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

dc.contributor.author	Al-Sharo Yasser Mohammad
dc.contributor.author	Abu-Jassar Amer Tahseen
dc.contributor.author	Sotnik, S.
dc.contributor.author	Lyashenko, V.
dc.date.accessioned	2021-10-09T10:58:40Z
dc.date.available	2021-10-09T10:58:40Z
dc.date.issued	2021
dc.description.abstract	The 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 presented	uk_UA
dc.identifier.citation	Al-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.issn	2231-5381
dc.identifier.uri	https://openarchive.nure.ua/handle/document/17864
dc.language.iso	en	uk_UA
dc.publisher	Seventh Sense Research Group	uk_UA
dc.subject	Neural Networks	uk_UA
dc.subject	recognition	uk_UA
dc.title	Neural Networks As A Tool For Pattern Recognition of Fasteners	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication