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2.1 KiB
2.1 KiB
SK-ResNeXt
SK ResNeXt is a variant of a ResNeXt that employs a Selective Kernel unit. In general, all the large kernel convolutions in the original bottleneck blocks in ResNext are replaced by the proposed SK convolutions, enabling the network to choose appropriate receptive field sizes in an adaptive manner.
{% 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{li2019selective,
title={Selective Kernel Networks},
author={Xiang Li and Wenhai Wang and Xiaolin Hu and Jian Yang},
year={2019},
eprint={1903.06586},
archivePrefix={arXiv},
primaryClass={cs.CV}
}