资源算法keras_resnext_fpn

keras_resnext_fpn

2020-02-24 | |  36 |   0 |   0

Keras Resnext Feature Pyramid Network

Feature Pyramid Network with ResNext backbone implemented in Keras. Use this for semantic segmentation tasks. Probably a good first step to get you up on those Kaggle competitions where everyone is still using regular Resnet FCNs ;)

Check the "Aggregated Residual Transformations for Deep Neural Networks" paper for info on ResNext

@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/bib/journals/corr/XieGDTH16},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

and "Feature Pyramid Networks for Object Detection" for info on FPNs:

@article{DBLP:journals/corr/LinDGHHB16,
  author    = {Tsung{-}Yi Lin and
               Piotr Doll{'{a}}r and
               Ross B. Girshick and
               Kaiming He and
               Bharath Hariharan and
               Serge J. Belongie},
  title     = {Feature Pyramid Networks for Object Detection},
  journal   = {CoRR},
  volume    = {abs/1612.03144},
  year      = {2016},
  url       = {http://arxiv.org/abs/1612.03144},
  archivePrefix = {arXiv},
  eprint    = {1612.03144},
  timestamp = {Mon, 13 Aug 2018 16:48:50 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/LinDGHHB16},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}


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