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Classification rejection by prediction

  • Lassus H. de 
  • Daigremont Ph. 
  • Badran F. 
  • Thiria S. 
  • Lecacheux A. 
Oral Presentations: Sensory Processing Sensory Processing I: Classification
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1112)

Abstract

We address the problem of autonomous decision making in classification of radioastronomy spectrograms from spacecraft. It is known that the assessment of the decision process can be divided into acceptation of the classification, instant rejection of the current signal classification, or rejection of the entire classifier model. We propose to combine prediction and classification with a double architecture of Time Delay Neural Network (TDNN) to optimize a decision minimizing the false alarm risk. Results on real data from URAP experiment aboard Ulysses spacecraft show that this scheme is tractable and effective.

Keywords

spectrogram classification radioastronomy neural network classification transient signal prediction 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Lassus H. de 
    • 1
  • Daigremont Ph. 
    • 2
  • Badran F. 
    • 2
  • Thiria S. 
    • 2
    • 3
  • Lecacheux A. 
    • 1
  1. 1.Laboratoire ARPEGESCNRS URA 1757, Observatoire de Paris-MeudonMeudon cedexFrance
  2. 2.Conservatoire National des Arts et MétiersCEDRICParisFrance
  3. 3.Laboratoire d'Océanographie et de Climatologie (LODYC)Université de Paris VIParisFrance

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