Interpretable CNNs for Object Classification

IEEE transactions on pattern analysis and machine intelligence, pp. 1-1, 2020.

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Abstract:

This paper proposes a generic method to learn interpretable convolutional filters in a deep convolutional neural network (CNN) for object classification, where each interpretable filter encodes features of a specific object part. Our method does not require additional annotations of object parts or textures for supervision. Instead, we us...More

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