U-Net was trained with limited data(20 image-mask pair).
U-Net is a convolutional neural network architecture designed for biomedical image segmentation tasks. Its unique "U" shape incorporates both downsampling and upsampling paths, enabling effective feature extraction and precise localization. U-Net has gained popularity for its ability to produce accurate segmentation masks, particularly in applications such as medical image analysis, where limited data is available.
