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An encoder–decoder deep neural network for binary segmentation of seismic facies.

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Title: An encoder–decoder deep neural network for binary segmentation of seismic facies.
Authors: Lima, Gefersom1, Zeiser, Felipe André1, da Silveira, Ariane2, Rigo, Sandro1,2, de Oliveira Ramos, Gabriel1, gdoramos@unisinos.br
Source: Computers & Geosciences; Jan2024, Vol. 183, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 174688143
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: An encoder–decoder deep neural network for binary segmentation of seismic facies.
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  Data: <searchLink fieldCode="AU" term="%22Lima%2C+Gefersom%22">Lima, Gefersom</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Zeiser%2C+Felipe+André%22">Zeiser, Felipe André</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22da+Silveira%2C+Ariane%22">da Silveira, Ariane</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Rigo%2C+Sandro%22">Rigo, Sandro</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AU" term="%22de+Oliveira+Ramos%2C+Gabriel%22">de Oliveira Ramos, Gabriel</searchLink><relatesTo>1</relatesTo>, <i>gdoramos@unisinos.br</i>
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=174688143
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.cageo.2023.105507
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: An encoder–decoder deep neural network for binary segmentation of seismic facies.
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            NameFull: Lima, Gefersom
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            NameFull: Zeiser, Felipe André
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            NameFull: da Silveira, Ariane
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            NameFull: Rigo, Sandro
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            NameFull: de Oliveira Ramos, Gabriel
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            – D: 15
              M: 01
              Text: Jan2024
              Type: published
              Y: 2024
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              Value: 00983004
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              Value: 183
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