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Improving person re-identification by multi-task learning.

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Bibliographic Details
Title: Improving person re-identification by multi-task learning.
Authors: Ling, Hefei1, Wang, Ziyang1, Li, Ping1, lpshome@hust.edu.cn, Shi, Yuxuan1, Chen, Jiazhong1, Zou, Fuhao1
Source: Neurocomputing; Jun2019, Vol. 347, p109-118, 10p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 136242255
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Improving person re-identification by multi-task learning.
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  Data: <searchLink fieldCode="AU" term="%22Ling%2C+Hefei%22">Ling, Hefei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Wang%2C+Ziyang%22">Wang, Ziyang</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Li%2C+Ping%22">Li, Ping</searchLink><relatesTo>1</relatesTo>, <i>lpshome@hust.edu.cn</i><br /><searchLink fieldCode="AU" term="%22Shi%2C+Yuxuan%22">Shi, Yuxuan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Chen%2C+Jiazhong%22">Chen, Jiazhong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Zou%2C+Fuhao%22">Zou, Fuhao</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Neurocomputing%22">Neurocomputing</searchLink>; Jun2019, Vol. 347, p109-118, 10p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=136242255
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.neucom.2019.01.027
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      – Code: eng
        Text: English
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        PageCount: 10
        StartPage: 109
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      – TitleFull: Improving person re-identification by multi-task learning.
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            NameFull: Ling, Hefei
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            NameFull: Wang, Ziyang
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            NameFull: Li, Ping
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            NameFull: Shi, Yuxuan
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            NameFull: Chen, Jiazhong
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              M: 06
              Text: Jun2019
              Type: published
              Y: 2019
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              Value: 347
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