This paper, Multi-label chest X-ray image classification via category-wise residual attention learning, appears in PATTERN RECOGNITION LETTERS, 2018. [Paper]

In this paper, we propose a category-wise residual attention learning (CRAL) framework. CRAL predicts the presence of multiple pathologies in a class-specific attentive view. The proposed framework consists of two modules: feature embedding module and attention learning module. The feature embedding module learns high-level features with a convolutional neural network (CNN) while the attention learning module focuses on exploring the assignment scheme of different categories.

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If you find the paper useful for your research, please consider cite:

@article{guan2018multi,
  title={Multi-label Chest X-ray Image Classification via Category-wise Residual Attention Learning},
  author={Guan, Qingji and Huang, Yaping},
  journal={Pattern Recognition Letters},
  year={2018},
  doi={https://doi.org/10.1016/j.patrec.2018.10.027},
  publisher={Elsevier}
}