Enhancing automated defect detection through sequential clustering and classification: a industrial case study using the sine-cosine algorithm, possibilistic fuzzy c-means, and artificial neural network

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Avtor(ji)

Nguyen, T. P. Q. (avtor)
Yang, C. L. (avtor)
Le, M. D. (avtor)
Nguyen, T. T. (avtor)
Luu, M. T. (avtor)

Jezik

angleški

Vir

Advances in production engineering and management

Leto

2023

Številčenje

letnik 18, številka 2

Vsebina

izdelava klešč kalsifikacija nevronske mreže odkrivanje napak

Založnik

Fakulteta za strojništvo, Inštitut za proizvodno strojništvo

Izvor

Univerza v Mariboru, Fakulteta za strojništvo
(Obvezni izvod spletne publikacije)

Pravice

URN

URN:NBN:SI:DOC-F2PC8HUS

COBISSID

268815107

DOI

10.14743/apem2023.2.470

Objavljeno

30.09.2026

Metapodatki

Citiranje

APA:

Nguyen, T. P. Q., Yang, C. L., Le, M. D., Nguyen, T. T., Luu, M. T. (2023). Enhancing automated defect detection through sequential clustering and classification: a industrial case study using the sine-cosine algorithm, possibilistic fuzzy c-means, and artificial neural network. Advances in production engineering and management, letnik 18, številka 2, str. 237-249. URN:NBN:SI:DOC-F2PC8HUS from http://www.dlib.si

MLA:

Nguyen, T. P. Q., Yang, C. L., Le, M. D., Nguyen, T. T., Luu, M. T.. "Enhancing automated defect detection through sequential clustering and classification: a industrial case study using the sine-cosine algorithm, possibilistic fuzzy c-means, and artificial neural network." Advances in production engineering and management letnik 18. številka 2 (2023) str. 237-249.
<http://www.dlib.si/?URN=URN:NBN:SI:DOC-F2PC8HUS>