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Enhancing the Effectiveness of Neural Networks in Predicting Railway Track Degradation
Sedghi, Mahdieh
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.
ORCID iD:
0000-0001-9681-3804
2024 (English)
In:
International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 651-664
Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2024. p. 651-664
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Computer graphics and computer vision
Research subject
Quality Technology and Logistics
Identifiers
URN:
urn:nbn:se:ltu:diva-103880
DOI:
10.1007/978-3-031-39619-9_48
Scopus ID:
2-s2.0-85181980921
OAI: oai:DiVA.org:ltu-103880
DiVA, id:
diva2:1830528
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, June 13-15, 2023
Available from:
2024-01-23
Created:
2024-01-23
Last updated:
2025-02-07
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Sedghi, Mahdieh
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ieee
modern-language-association-8th-edition
vancouver
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apa
ieee
modern-language-association-8th-edition
vancouver
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en-GB
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