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5.5 KiB
5.5 KiB
ResNet-D
ResNet-D is a modification on the ResNet architecture that utilises an average pooling tweak for downsampling. The motivation is that in the unmodified ResNet, the 1×1 convolution for the downsampling block ignores 3/4 of input feature maps, so this is modified so no information will be ignored
{% include 'code_snippets.md' %}
How do I train this model?
You can follow the timm recipe scripts for training a new model afresh.
Citation
@misc{he2018bag,
title={Bag of Tricks for Image Classification with Convolutional Neural Networks},
author={Tong He and Zhi Zhang and Hang Zhang and Zhongyue Zhang and Junyuan Xie and Mu Li},
year={2018},
eprint={1812.01187},
archivePrefix={arXiv},
primaryClass={cs.CV}
}