Learning Separable Filters with Shared Parts


Learned image features can provide great accuracy in many Computer Vision tasks. However, when the convolution filters used to learn image features are numerous and not separable, feature extraction becomes computationally demanding and impractical to use in real-world situations. In this thesis work, a method for learning a small number of separable… (More)


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