Handwritten Digit Recognition with a Novel Vision Model that Extracts Linearly Separable Features
نویسندگان
چکیده
We use well-established results in biological vision to construct a novel vision model for handwritten digit recognition. We show empirically that the features extracted by our model are linearly separable over a large training set (MNIST). Using only a linear classifier on these features, our model is relatively simple yet outperforms other models on the same data set.
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