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The link you provided is associated with a dataset or resource used in a specific research paper on . Associated Research Paper
: Published in Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support (DLMIA), a workshop held in conjunction with MICCAI 2018. Why the Link is Likely Dead https://www107.zippyshare.com/v/ZGtYsP8M/file.html
The specific file ID in your URL ( ZGtYsP8M ) was frequently shared in academic and developer communities (such as GitHub repositories) as a mirror for the or a specific subset of the Cell Nuclei dataset (from the 2018 Data Science Bowl) used to evaluate the UNet++ model. Key Details of the Paper The link you provided is associated with a
: Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang. Key Details of the Paper : Zongwei Zhou,
: To improve medical image segmentation by using a "nested" and "dense" architecture that bridges the semantic gap between the encoder and decoder feature maps.
The "proper paper" related to that file is by Zhou et al. (2018).
The hosting service Zippyshare officially . Files hosted there are no longer accessible. If you are looking for the content that was in that file, you should refer to the official UNet++ GitHub repository or the original dataset on Kaggle .
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