AI/U-2-Net
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@ -14,6 +14,8 @@ __Contact__: xuebin[at]ualberta[dot]ca
## Updates !!! ## Updates !!!
**（2020-Sep-13)** Our U^2-Net based model is the **6th** in [**MICCAI 2020 Thyroid Nodule Segmentation Challenge**](https://tn-scui2020.grand-challenge.org/Resultannouncement/).
**(2020-May-18)** The official paper of our **U^2-Net (U square net)** ([**PDF in elsevier**(free until July 5 2020)](https://www.sciencedirect.com/science/article/pii/S0031320320302077?dgcid=author), [**PDF in arxiv**](http://arxiv.org/abs/2005.09007)) is now available. If you are not able to access that, please feel free to drop me an email. **(2020-May-18)** The official paper of our **U^2-Net (U square net)** ([**PDF in elsevier**(free until July 5 2020)](https://www.sciencedirect.com/science/article/pii/S0031320320302077?dgcid=author), [**PDF in arxiv**](http://arxiv.org/abs/2005.09007)) is now available. If you are not able to access that, please feel free to drop me an email.
**(2020-May-16)** We fixed the upsampling issue of the network. Now, the model should be able to handle **arbitrary input size**. (Tips: This modification is to facilitate the retraining of U^2-Net on your own datasets. When using our pre-trained model on SOD datasets, please keep the input size as 320x320 to guarantee the performance.) **(2020-May-16)** We fixed the upsampling issue of the network. Now, the model should be able to handle **arbitrary input size**. (Tips: This modification is to facilitate the retraining of U^2-Net on your own datasets. When using our pre-trained model on SOD datasets, please keep the input size as 320x320 to guarantee the performance.)