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pytorch-image-models/docs/models/.templates/models/gloun-resnext.md

4.4 KiB

(Gluon) ResNeXt

A ResNeXt repeats a building block that aggregates a set of transformations with the same topology. Compared to a ResNet, it exposes a new dimension, cardinality (the size of the set of transformations) C, as an essential factor in addition to the dimensions of depth and width.

The weights from this model were ported from Gluon.

{% include 'code_snippets.md' %}

How do I train this model?

You can follow the timm recipe scripts for training a new model afresh.

Citation

@article{DBLP:journals/corr/XieGDTH16,
  author    = {Saining Xie and
               Ross B. Girshick and
               Piotr Doll{\'{a}}r and
               Zhuowen Tu and
               Kaiming He},
  title     = {Aggregated Residual Transformations for Deep Neural Networks},
  journal   = {CoRR},
  volume    = {abs/1611.05431},
  year      = {2016},
  url       = {http://arxiv.org/abs/1611.05431},
  archivePrefix = {arXiv},
  eprint    = {1611.05431},
  timestamp = {Mon, 13 Aug 2018 16:45:58 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/XieGDTH16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}