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# DA_fMedical_Survey |
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DML Git page for the paper "Domain Adaptation and Generalization on Functional Medical Images: A
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Systematic Survey" |
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DML Git page for the paper "Domain Adaptation and Generalization on Functional Medical Images: A |
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Systematic Survey" |
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This GitHub repository provides a systematic overview of novel domain adaptation and domain generalization methods on functional brain images. It contains a variety of resources and papers to help researchers and practitioners understand and apply these methods in their own projects. The repository also contains tables and references related to novel domain adaptation and generalization techniques, as well as a collection of related datasets. This repository is a valuable resource for anyone interested in exploring and exploiting the field of domain adaptation and domain generalization on functional brain images. |
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# Contents |
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* Table of papers |
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* Table of Datasets |
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* New papers |
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# Cite |
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[Arxiv version of paper](https://arxiv.org/abs/2212.03176): |
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``` |
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@misc{https://doi.org/10.48550/arxiv.2212.03176, |
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doi = {10.48550/ARXIV.2212.03176}, |
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url = {https://arxiv.org/abs/2212.03176}, |
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author = {Sarafraz, Gita and Behnamnia, Armin and Hosseinzadeh, Mehran and Balapour, Ali and Meghrazi, Amin and Rabiee, Hamid R.}, |
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keywords = {Image and Video Processing (eess.IV), Computer Vision and Pattern Recognition (cs.CV), Machine Learning (cs.LG), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Computer and information sciences, FOS: Computer and information sciences}, |
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title = {Domain Adaptation and Generalization on Functional Medical Images: A Systematic Survey}, |
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publisher = {arXiv}, |
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year = {2022}, |
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copyright = {arXiv.org perpetual, non-exclusive license} |
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} |
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``` |