Number of the records: 1  

Active Learning for LSTM-autoencoder-based Anomaly Detection in Electrocardiogram Readings

  1. SYS0536614
    LBL
      
    01000a^^22220027750^450
    005
      
    20240103225011.9
    014
      
    $a 85091975806 $2 SCOPUS
    100
      
    $a 20201222d m y slo 03 ba
    101
      
    $a eng
    102
      
    $a DE
    200
    1-
    $a Active Learning for LSTM-autoencoder-based Anomaly Detection in Electrocardiogram Readings
    215
      
    $a 6 s. $c E
    463
    -1
    $1 001 cav_un_epca*0536611 $1 011 $a 1613-0073 $1 200 1 $a Proceedings of the Workshop on Interactive Adaptive Learning $v S. 72-77 $1 210 $a Aachen $c Technical University & CreateSpace Independent Publishing $d 2020 $1 225 $a CEUR Workshop Proceedings $v 2660 $1 702 1 $a Kottke $b D. $4 340 $1 702 1 $a Krempl $b G. $4 340 $1 702 1 $a Lemaire $b V. $4 340 $1 702 1 $a Holzinger $b A. $4 340 $1 702 1 $a Calma $b A. $4 340
    610
      
    $a Active Learning
    610
      
    $a Anomaly detection
    610
      
    $a LSTM-Autoencoder
    610
      
    $a Time series
    700
    -1
    $3 cav_un_auth*0333682 $a Šabata $b T. $y CZ
    701
    -1
    $3 cav_un_auth*0100761 $a Holeňa $b Martin $p UIVT-O $i Oddělení strojového učení $j Department of Machine Learning $w Department of Machine Learning $T Ústav informatiky AV ČR, v. v. i.
    856
      
    $u http://ceur-ws.org/Vol-2660/ialatecml_shortpaper1.pdf $9 RIV
Number of the records: 1  

  This site uses cookies to make them easier to browse. Learn more about how we use cookies.