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Fusion of Heterogeneous Data in Convolutional Networks for Urban Semantic Labeling (Invited Paper)

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 نشر من قبل Nicolas Audebert
 تاريخ النشر 2017
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English
 تأليف Nicolas Audebert




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In this work, we present a novel module to perform fusion of heterogeneous data using fully convolutional networks for semantic labeling. We introduce residual correction as a way to learn how to fuse predictions coming out of a dual stream architecture. Especially, we perform fusion of DSM and IRRG optical data on the ISPRS Vaihingen dataset over a urban area and obtain new state-of-the-art results.



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