基于深度学习的铁路车轮踏面检验样板粗糙度分类识别方法.

Saved in:
Bibliographic Details
Title: 基于深度学习的铁路车轮踏面检验样板粗糙度分类识别方法. (Chinese)
Authors: 卢 欣1, 马婷婷1, 谢嘉亮1, 谭 颖1
Source: Mechanical & Electrical Engineering Technology; Nov2025, Vol. 54 Issue 21, p88-95, 8p
Database: Applied Science & Technology Source
FullText Text:
  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 190310462
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: 基于深度学习的铁路车轮踏面检验样板粗糙度分类识别方法. (Chinese)
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22卢+欣%22">卢 欣</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22马婷婷%22">马婷婷</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22谢嘉亮%22">谢嘉亮</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22谭+颖%22">谭 颖</searchLink><relatesTo>1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Mechanical+%26+Electrical+Engineering+Technology%22">Mechanical & Electrical Engineering Technology</searchLink>; Nov2025, Vol. 54 Issue 21, p88-95, 8p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=190310462
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3969/j.issn.1009-9492.2025.21.016
    Languages:
      – Code: chi
        Text: Chinese
    PhysicalDescription:
      Pagination:
        PageCount: 8
        StartPage: 88
    Titles:
      – TitleFull: 基于深度学习的铁路车轮踏面检验样板粗糙度分类识别方法.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: 卢 欣
      – PersonEntity:
          Name:
            NameFull: 马婷婷
      – PersonEntity:
          Name:
            NameFull: 谢嘉亮
      – PersonEntity:
          Name:
            NameFull: 谭 颖
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 10099492
          Numbering:
            – Type: volume
              Value: 54
            – Type: issue
              Value: 21
          Titles:
            – TitleFull: Mechanical & Electrical Engineering Technology
              Type: main
ResultId 1