Presentation Open Access

A deep learning approach to anomaly detection in nuclear reactors

Francesco Caliva


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.1410092", 
  "language": "eng", 
  "title": "A deep learning approach to anomaly detection in nuclear reactors", 
  "issued": {
    "date-parts": [
      [
        2018, 
        7, 
        13
      ]
    ]
  }, 
  "abstract": "<p>Presented at IJCNN 2018, this presentation contains&nbsp;the description of a novel deep learning approach to unfold nuclear power reactor signals is proposed. It includes a combination of convolutional neural networks (CNN), denoising autoencoders (DAE) and k-means clustering of representations.</p>", 
  "author": [
    {
      "family": "Francesco Caliva"
    }
  ], 
  "type": "speech", 
  "id": "1410092"
}
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