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Subject: Anomaly Detection Item type: Thesis Supervisors: Dick, Scott (Electrical and Computer Engineering)

  • Anomaly Detection Using Deep Learning

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    Spring 2021

    Reshadi, Mohammadhossein

    Deep learning has revolutionized many fields that process large amounts of data such as images, video, audio, speech, and text. Anomaly detection, however, is among the areas that still require major advancements. Based on the key traits of deep learning, which are the need for very little hand...

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