; ;
In
17th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME ‘23) / Edited by Roberto Teti Prof. 9798331306984
In
Procedia CIRP 126, Seiten/Artikel-Nr.:360-365
2024
Einrichtungen
Projekte
Inhaltliche Beschreibung (Schlagwörter)
BIB2TF100 (frei) ; ZSPNTF100 (frei)
Thematische Einordnung (Klassifikation)
DDC: 670
Dokumenttyp
Journal Article (Review Article)/Contribution to a book/Contribution to a conference proceedings
Format
print
Sprache
English
Anmerkung
Peer reviewed article
Interne Identnummern
RWTH-2025-03724
Datensatz-ID: 1009863
Beteiligte Länder
Germany
Conference Presentation
Deep Learning Approach for Enhanced Transferability and Learning Capacity in Tool Wear Estimation
17. CIRP International Conference on Intelligent Computation in Manufacturing Engineering, ICME 2023, NeapelNeapel, Germany, 12 Jul 2023 - 14 Jul 2023
Files
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EndNote:
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RIS
Journal Article (Review Article)/Contribution to a conference proceedings
Deep Learning Approach for Enhanced Transferability and Learning Capacity in Tool Wear Estimation
17. CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2023, IschiaIschia, Italy, 12 Jul 2023 - 14 Jul 2023
Procedia CIRP 126, 360-365 (2024) [10.1016/j.procir.2024.08.376] special issue: "17th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME ‘23) / Edited by Roberto Teti Prof."
Files
BibTeX |
EndNote:
XML,
Text |
RIS