Semi-supervised Multi-domain Learning for Medical Image Classification

The limitations of domain dependence in neural networks and data scarcity are addressed in this paper by analyzing the problem of semi-supervised medical image classification across multiple visual domains using a single integrated framework. Under this premise, we learn a universal parametric family of neural networks, which share a majority of their weights across domains by learning a few adaptive domain-specific parameters.

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@inproceedings{chavhan2023semi,
  title={Semi-supervised Multi-domain Learning for Medical Image Classification},
  author={Chavhan, Ruchika and Banerjee, Biplab and Das, Nibaran},
  booktitle={Recent Trends in Image Processing and Pattern Recognition: 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 1-2, 2022, Revised Selected Papers},
  year={2023},
}