Saccader: Improving Accuracy of Hard Attention Models for Vision

    Gamaleldin Elsayed
    Gamaleldin Elsayed
    Simon Kornblith
    Simon Kornblith

    NeurIPS, 2019.

    Cited by: 1|Bibtex|Views32|Links

    Abstract:

    Although deep convolutional neural networks achieve state-of-the-art performance across nearly all image classification tasks, their decisions are difficult to interpret. One approach that offers some level of interpretability by design is hard attention, which uses only relevant portions of the image. However, training hard attention mod...More

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