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Handwritten digit recognition with a novel vision model that extracts linearly separable features

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2 Author(s)
Loo-Nin Teow ; Sch. of Comput., Nat. Univ. of Singapore, Singapore ; Kia-Fock Loe

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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Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on  (Volume:2 )

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