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UTILIZING CONVOLUTIONAL NEURAL NETWORKS FOR CLASSIFYING WIRE PLASTIC DEFORMATION TECHNIQUE

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NOVEMBER 2025   -  Volume: 100 -  Pages: 470

DOI:

https://doi.org/10.52152/D11131

Authors:

MATHEUS CAPELIN
-
ARTHUR D. K. RODRIGUES
-
GIULIANA DE LIMA MARCONDES MONTEIRO
-
GUSTAVO ARISTIDES SANTANA MARTINEZ
-
LUIZ TADEU FERNANDES ELENO
-
WEI LIANG QIAN

Disciplines:

  • INFORMATION TECHNOLOGY AND KNOWLEDGE (INTELIGENCIA ARTIFICIAL Y SIMULACION )
  • Solid state physics (ESTRUCTURA CRISTALINA )
  • Industrial technology (INGENIERIA DE PROCESOS )

Downloads:   16

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Key words:
machine learning, convolutional neural network, image processing, wire plastic deformation processes, CNN, aprendizaje automático, red neuronal convolucional, procesamiento de imágenes, procesos de deformación plástica del alambre
Article type:
NOTA TECNICA / TECHNICAL NOTE
Section:
TECHNICAL NOTE

Improving productivity and quality requires technological and process innovation, particularly in cold wire plastic deformation methods such as Rotary Swaging (RS) and Wire Rolling Cassetetes (WRC).

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