Indirect cutting tool wear classification using deep learning and chip colour analysis

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1433-3015

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Indirect cutting tool wear classification using deep learning and chip colour analysis ; volume:111 ; number:3-4 ; day:7 ; month:10 ; year:2020 ; pages:1099-1114 ; date:11.2020
The international journal of advanced manufacturing technology ; 111, Heft 3-4 (7.10.2020), 1099-1114, 11.2020

Creator: Pagani, Luca
Parenti, Paolo
Cataldo, Salvatore
Scott, Paul J.
Annoni, Massimiliano

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00170-020-06055-6

URN: urn:nbn:de:101:1-2020112818052266322190

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:38 AM CEST

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Pagani, Luca
Parenti, Paolo
Cataldo, Salvatore
Scott, Paul J.
Annoni, Massimiliano
SpringerLink (Online service)

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Indirect cutting tool wear classification using deep learning and chip colour analysis

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Other Objects (12)

Study of using cutting chip color to the tool wear prediction

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Data-driven indirect punch wear monitoring in sheet-metal stamping processes

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