Corpus ID: 1023605

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

@article{Szegedy2017Inceptionv4IA,
  title={Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning},
  author={Christian Szegedy and S. Ioffe and V. Vanhoucke and Alexander Amir Alemi},
  journal={ArXiv},
  year={2017},
  volume={abs/1602.07261}
}
  • Christian Szegedy, S. Ioffe, +1 author Alexander Amir Alemi
  • Published 2017
  • Computer Science
  • ArXiv
  • Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years. [...] Key Method We also present several new streamlined architectures for both residual and non-residual Inception networks. These variations improve the single-frame recognition performance on the ILSVRC 2012 classification task significantly. We further demonstrate how proper activation scaling stabilizes the training of very wide residual Inception networks. With an ensemble of three…Expand Abstract
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