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ELUnet-and-his-Encoder

The official code for "COVID-19 CT Images Segmentation". Unet++ with ELU activision as Decoder and MobileNet V3 mobile as Encoder Unet++ with ELU activision as Decoder and NasNet mobile as Encoder Unet++ with ELU activision as Decoder and EfficientNetB0 as Encoder

Updates

Citation

@article{
  year={2023}
}

How to use

first download models and save them in same directory with IPYNB file as jupyter notebooks then Run nootbooks.

Model weights

Kaggle Drive Link:().

Training and Testing

  1. Download the face mask detection dataset from here.

    1. Run the following code to install the Requirements.

    pip install -r requirements.txt

  3. Run the below code to train the Unet++ with ELU activision as Decoder and... as Encoder with this dataset.

Unet++ with ELU activision as Decoder and MobileNet V3 mobile as Encoder Unet++ with ELU activision as Decoder and NasNet mobile as Encoder Unet++ with ELU activision as Decoder and EfficientNetB0 as Encoder

  1. Test trained model with this dataset in in IPYNB too.

Results

Performance comparision on covid-segmentation dataset.