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- W4321122241 abstract "This paper proposes a novel loss function inspired by the Tversky-Kahneman probability weighting function to effectively deal with medical image segmentation tasks. The proposed loss, which is called Tversky-Kahneman loss function, is assessed on the official Skin Lesion datasets of the ISIC 2017 and ISIC 2018 Challenge. To evaluate our new loss function, we propose modified U-Net-based model to obtain quantitative results in Dice score and Jaccard index. Various experiments indicate that our new loss function provides a more promising and time-saving performance than other loss functions." @default.
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- W4321122241 date "2023-01-01" @default.
- W4321122241 modified "2023-10-16" @default.
- W4321122241 title "Tversky-Kahneman: A New Loss Function for Skin Lesion Image Segmentation" @default.
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- W4321122241 doi "https://doi.org/10.1007/978-981-19-6631-6_14" @default.
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