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J-GLOBAL ID：202102284640692444   Reference number：21A0520934

Unsupervised Anomaly Detection in Flight Data Using Convolutional Variational Auto-Encoder

畳込み変分自動エンコーダを用いた飛行データにおける教師なし異常検出【JST・京大機械翻訳】

Author (3)： Memarzadeh Milad (Data Sciences Group, NASA Ames Research Center, USRA, Moffett Field, CA 94035, USA) ,  Matthews Bryan (Data Sciences Group, NASA Ames Research Center, KBR Inc., Moffett Field, CA 94035, USA) ,  Avrekh Ilya (Data Sciences Group, NASA Ames Research Center, KBR Inc., Moffett Field, CA 94035, USA)
Material： Aerospace (Web)
Volume： 7  Issue： 8  Page： 115  Publication year： 2020 
JST Material Number： U7127A  ISSN： 2226-4310  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： The modern National Airspace S...

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Thesaurus term： *convolution ,  *variational method ,  Learning ,  air transportation ,  supervised learning ,  *coder ,  producer ,  *flight ,  case study ,  higher dimension ,  flight data ,  Machine Learning ,  airline ,  generation model
Semi thesaurus term： イベント検出 , 【Automatic Indexing@JST】

Author keywords (4)： anomaly detection ,  variational autoencoder ,  flight safety ,  time series

JST classification (2)： Air traffic control,air navigation facilities  (TE01030T) ,  General  (TE01010X)

Reference (31)：

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Terms in the title (6)： 畳込み ,  変分 ,  エンコーダ ,  飛行データ ,  教師 ,  異常検出