ResCNet

模型架构文件在src文件夹下。

本仓库可用的模型列表：

# for imagenet
rescnet18, rescnet34, rescnet50 

# for cifar
rescnet32, rescnet56
rescnet50_c100

可训练的脚本文件请移步：https://github.com/tcmyxc/CV-Tutorial

Citation

If you find the paper useful in your research, please consider citing:

@article{xu2025deep,
  title={Deep feature response discriminative calibration},
  author={Xu, Wenxiang and Qiu, Tian and Zhou, Linyun and Feng, Zunlei and Song, Mingli and Wang, Huiqiong},
  journal={Neurocomputing},
  volume={615},
  pages={128848},
  year={2025},
  publisher={Elsevier}
}