Convolutional Neural Networks

Inception-v3

Introduced by Szegedy et al. in Rethinking the Inception Architecture for Computer Vision

Inception-v3 is a convolutional neural network architecture from the Inception family that makes several improvements including using Label Smoothing, Factorized 7 x 7 convolutions, and the use of an auxiliary classifer to propagate label information lower down the network (along with the use of batch normalization for layers in the sidehead).

Source: Rethinking the Inception Architecture for Computer Vision

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