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    Dissecting Convolutional Neural Networks

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    WHITAKER-HONORSTHESIS-2018.pdf (485.1Kb)

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    Author
    Whitaker, Justin Daniel
    Abstract
    I examined the hidden layers of a convolutional neural network for MNIST handwritten digit classification. I found that it is possible to view how backpropagation affects nodes in the activation maps of hidden layers by visualizing their outputs as images across training epochs. This can allow one to look inside the black box of neural networks and to gain a deeper understanding of their mechanics.
    URI
    http://hdl.handle.net/10342/7293
    Subject
     machine learning; neural network; convolutional; supervised learning 
    Date
    2019-06-12
    Citation:
    APA:
    Whitaker, Justin Daniel. (June 2019). Dissecting Convolutional Neural Networks (Honors Thesis, East Carolina University). Retrieved from the Scholarship. (http://hdl.handle.net/10342/7293.)

    Display/Hide MLA, Chicago and APA citation formats.

    MLA:
    Whitaker, Justin Daniel. Dissecting Convolutional Neural Networks. Honors Thesis. East Carolina University, June 2019. The Scholarship. http://hdl.handle.net/10342/7293. August 10, 2022.
    Chicago:
    Whitaker, Justin Daniel, “Dissecting Convolutional Neural Networks” (Honors Thesis., East Carolina University, June 2019).
    AMA:
    Whitaker, Justin Daniel. Dissecting Convolutional Neural Networks [Honors Thesis]. Greenville, NC: East Carolina University; June 2019.
    Collections
    • Honors College
    Publisher
    East Carolina University

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