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Author (up) Parichehr Behjati Ardakani; Diego Velazquez; Josep M. Gonfaus; Pau Rodriguez; Xavier Roca; Jordi Gonzalez edit   pdf
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  Title Catastrophic interference in Disguised Face Recognition Type Conference Article
  Year 2019 Publication 9th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 11868 Issue Pages 64-75  
  Keywords Neural network forgetness; Face recognition; Disguised Faces  
  Abstract It is commonly known the natural tendency of artificial neural networks to completely and abruptly forget previously known information when learning new information. We explore this behaviour in the context of Face Verification on the recently proposed Disguised Faces in the Wild dataset (DFW). We empirically evaluate several commonly used DCNN architectures on Face Recognition and distill some insights about the effect of sequential learning on distinct identities from different datasets, showing that the catastrophic forgetness phenomenon is present even in feature embeddings fine-tuned on different tasks from the original domain.  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference IbPRIA  
  Notes ISE; 600.098; 600.119 Approved no  
  Call Number Admin @ si @ AVG2019 Serial 3416  
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