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.

2. 2. 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

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

Results

Performance comparision on covid-segmentation dataset.