Conference
View in EDS

Gender classification of subjects from cerebral blood flow changes using Deep Learning

Bibliographic Details
Title: Gender classification of subjects from cerebral blood flow changes using Deep Learning
Authors: Hiroyasu, Tomoyuki, Hanawa, Kenya, Yamamoto, Utako
Source: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on. :229-233 Dec, 2014
Relation: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
Database: IEEE Xplore Digital Library
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://login.libproxy.scu.edu/login?url=https://ieeexplore.ieee.org/document/7008672
    Name: EDS - IEEE (s8985755)
    Category: fullText
    Text: Check IEEE Xplore for full text
    MouseOverText: Check IEEE Xplore for full text. A new window will open.
  – Url: https://resolver.ebsco.com/c/xy5jbn/result?sid=EBSCO:edseee&genre=book&issn=edseee.IEEEConferenc&ISBN=9781479945184&volume=&issue=&date=&spage=229&pages=229-233&title=2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on&atitle=Gender%20classification%20of%20subjects%20from%20cerebral%20blood%20flow%20changes%20using%20Deep%20Learning&aulast=Hiroyasu%2C%20Tomoyuki&id=DOI:10.1109/CIDM.2014.7008672
    Name: Full Text Finder (for New FTF UI) (s8985755)
    Category: fullText
    Text: Find It @ SCU Libraries
    MouseOverText: Find It @ SCU Libraries
Header DbId: edseee
DbLabel: IEEE Xplore Digital Library
An: edseee.7008672
RelevancyScore: 975
AccessLevel: 2
PubType: Conference
PubTypeId: conference
PreciseRelevancyScore: 974.66455078125
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Gender classification of subjects from cerebral blood flow changes using Deep Learning
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hiroyasu%2C+Tomoyuki%22">Hiroyasu, Tomoyuki</searchLink><br /><searchLink fieldCode="AR" term="%22Hanawa%2C+Kenya%22">Hanawa, Kenya</searchLink><br /><searchLink fieldCode="AR" term="%22Yamamoto%2C+Utako%22">Yamamoto, Utako</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on. :229-233 Dec, 2014
– Name: NoteTitleSource
  Label: Relation
  Group: SrcInfo
  Data: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
PLink https://login.libproxy.scu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edseee&AN=edseee.7008672
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1109/CIDM.2014.7008672
    PhysicalDescription:
      Pagination:
        PageCount: 5
        StartPage: 229
    Titles:
      – TitleFull: Gender classification of subjects from cerebral blood flow changes using Deep Learning
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hiroyasu, Tomoyuki
      – PersonEntity:
          Name:
            NameFull: Hanawa, Kenya
      – PersonEntity:
          Name:
            NameFull: Yamamoto, Utako
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Type: published
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9781479945184
            – Type: issn-locals
              Value: edseee.IEEEConferenc
          Titles:
            – TitleFull: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on
              Type: main
ResultId 1