Sep 21, 2021 · We propose a novel training methodology -- Concept Group Learning (CGL) -- that encourages training of interpretable CNN filters by ...
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We propose a novel training methodology—. Concept Group Learning (CGL)—that encourages training of interpretable CNN filters by partition-.
Sep 21, 2021 · We propose a novel training methodology— Concept Group Learning (CGL)—that encourages training of interpretable CNN filters by partition- ing ...
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Learning disentangled filters in CNNs alleviates filter-class entanglement and meanwhile narrows the gap between human concept and CNN's representations. In ...
Get images with human-labeled visual concepts, from stripes to skyscrapers. Measure the CNN channel activations for these images. Quantify the alignment of ...
We propose a novel training methodology-Concept Group Learning (CGL)-that encourages training of interpretable CNN filters by partitioning filters in each ...
Oct 19, 2023 · We present a novel kernel grouping algorithm and show that grouping similar kernels leads to a significant reduction in the size of the rule-set ...
This paper proposes a method to modify a tradi- tional convolutional neural network (CNN) into an interpretable compositional CNN, in order to learn filters ...
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Jul 14, 2023 · Unlike current ensembles, the models constructed by EPU-CNN enables interpretable classification based both on perceptual features and their ...