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UNet-CAA
Marinheiro2004/UNet-CAA
UNet-CAA is a machine learning model from Marinheiro2004. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
- Base: U-Net - Encoder: ResNet34 (pretrained) - Input: 3 channels, 512×512 - Output: 1 channel
Access
Public
Updated Mar 8, 2026
Parameters
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At a glance
- Access
- Public
- Created
- Mar 8, 2026
- Updated
- Mar 8, 2026
- SHA
- 1b420334
Model card
From the Hugging Face model README
UNet Kvasir-SEG
Architecture
- Base: U-Net
- Encoder: ResNet34 (pretrained)
- Input: 3 channels, 512×512
- Output: 1 channel
Loss function
- Dice Loss
Dataset
- Kvasir-SEG
- Train/Val/Test: dataset default split
Preprocessing
- Resize 512×512
- Data augmentation: HorizontalFlip, VerticalFlip, RandomRotate90, RandomBrightnessContrast
Notes
- Model trained with 100 epochs
- Best checkpoint based on Dice Loss Validation
Config
{
"in_channels": 3,
"num_classes": 1,
"encoder": "resnet34",
"img_size": 512
}
Performance
- Best validation Dice Loss: 0.122
- Corresponding Dice Score ≈ 0.878
- Created
- Mar 8, 2026
- Updated
- Mar 8, 2026