Inception-v3
Inception-v3
**Inception-v3** is a convolutional neural network architecture from the Inception family that makes several improvements including using [Label Smoothing](https://paperswithcode.com/method/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](https://paperswithcode.com/method/batch-normalization) for layers in the sidehead).
Rethinking the Inception Architecture for Computer Vision
https://paperswithcode.com/paper/rethinking-the-inception-architecture-for
Rethinking the Inception Architecture for Computer Vision