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    Neural network watchdog for out-of-distribution input mitigation.

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    Date
    2021-10-19
    Author
    Bui, Justin M., 1988-
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    Abstract
    Neural networks have often been described as black boxes. The prevalence of publicly available neural networks and the application of transfer learning has allowed for the development of systems with minimal understanding of the data distribution. For example, a generic neural network trained to differentiate between kittens and puppies will classify a picture of a kumquat as either a kitten or a puppy, despite the kumquat residing outside the known data distribution. The neural network watchdog is a technique which screens trained classifier and regression machine input candidates to determine the distribution validity, and allows for methods of out-of-distribution removal with minimal performance impact.
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    https://hdl.handle.net/2104/11704
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    Copyright © Baylor® University All rights reserved. Legal Disclosures.
    Baylor University Waco, Texas 76798 1-800-BAYLOR-U
    Baylor University Libraries | One Bear Place #97148 | Waco, TX 76798-7148 | 254.710.2112 | Contact: libraryquestions@baylor.edu
    If you find any errors in content, please contact librarywebmaster@baylor.edu
    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
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    Theme by 
    Atmire NV