> ## Documentation Index
> Fetch the complete documentation index at: https://aegean.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# UNet Semantic Segmentation
> Introduction to the UNet architecture for semantic segmentation.
**Key references**: (Yuan et al., 2019; Ibrahim et al., 2018; Zhao et al., 2019; Cordts et al., 2016; Li et al., 2018)
Build UNet in PyTorch, DoubleConv, Down, Up, OutConv blocks, Dice + CE loss, Oxford-IIIT Pet segmentation.
## References
* Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., et al. (2016). *The Cityscapes Dataset for Semantic Urban Scene Understanding*.
* Ibrahim, M., Vahdat, A., Ranjbar, M., Macready, W. (2018). *Semi-Supervised Semantic Image Segmentation with Self-correcting Networks*.
* Li, Y., Shi, J., Lin, D. (2018). *Low-Latency Video Semantic Segmentation*.
* Yuan, Y., Chen, X., Chen, X., Wang, J. (2019). *Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation*.
* Zhao, S., Wang, Y., Yang, Z., Cai, D. (2019). *Region mutual information loss for semantic segmentation*.
***
[Edit this page on GitHub](https://github.com/aegean-ai/eaia/edit/main/src/aiml-common/lectures/scene-understanding/semantic-segmentation/unet/index.mdx) or [file an issue](https://github.com/aegean-ai/eaia/issues/new/choose).