Presentation Open Access

A deep learning approach to anomaly detection in nuclear reactors

Francesco Caliva

Presented at IJCNN 2018, this presentation contains 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.

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