Spectrewolf8/UNET-50-aerial-image-road-segmentation-xp
A U-Net-50 model for segmenting road networks in aerial images. Trained on the Massachusetts Roads Dataset, the model accurately identifies and segments roads, making it ideal for applications in urban planning and autonomous driving
No commits in the last 6 months.
Stars
4
Forks
—
Language
Jupyter Notebook
License
MIT
Last pushed
Aug 12, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/Spectrewolf8/UNET-50-aerial-image-road-segmentation-xp"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
qubvel-org/segmentation_models.pytorch
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
OSUPCVLab/SegFormer3D
Official Implementation of SegFormer3D: an Efficient Transformer for 3D Medical Image...
tue-mps/eomt
[CVPR 2025 Highlight] Official code and models for Encoder-only Mask Transformer (EoMT).
jeya-maria-jose/Medical-Transformer
Official Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image...
davidiommi/Pytorch--3D-Medical-Images-Segmentation--SALMON
Segmentation deep learning ALgorithm based on MONai toolbox: single and multi-label segmentation...