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Deep Learning Classification With Noisy Labels
Deep Learning systems have shown tremendous accuracy in image classification, at the cost of big image datasets.
Fourier descriptors based on the structure of the human primary visual cortex with applications to object recognition
In this paper we propose a supervised object recognition method using new global features and inspired by the model of the human primary visual cortex V1 as the semidiscrete roto-translation group $SE(2, N) = \mathbb Z_N\rtimes \mathbb R^2$.
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