VGG16-U-NET Model Card

Model Description

Model Name: VGG16-U-NET

Model Type: Image Segmentation

Architecture: U-Net with VGG16 weights trained on Imagenet

Model Performance

Metric	Value
Accuracy	0.9815
Intersection Over Union (IoU)	0.9509
Dice Score	0.9794

Training Details

Dataset: tangez/ain3007

Training Parameters:

• Architecture: U-Net with VGG16 encoder backbone
• Pre-trained weights: ImageNet
• Framework: PyTorch

Intended Use

Primary Use Cases:

• Image segmentation tasks

How to Use

import torch

# Load the trained model from the Models directory
model = torch.load("path/to/model.pth")
model.eval()

# For inference on WSI patches
with torch.no_grad():
    output = model(input_patches)
    # Output will be binary tissue masks