Titlebook: Domain Adaptation and Representation Transfer; 5th MICCAI Workshop, Lisa Koch,M. Jorge Cardoso,Dong Yang Conference proceedings 2024 The Ed

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Unilateral Biportal Endoscopy of the Spinem large ones. As the number of DL architectures explodes, exhaustively attempting all candidates becomes unfeasible, motivating cheaper alternatives for choosing them. Transferability scoring methods emerge as an enticing solution, allowing to efficiently calculate a score that correlates with the a

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dominant

Unilateral Biportal Endoscopy of the Spineecent Deep Learning solutions, which can hinder future adoption. Particularly, the vulnerability of Vision Transformer (ViT) to adversarial, privacy, and confidentiality attacks raise serious concerns about their reliability in medical settings. This work aims to enhance the robustness of self-ensem

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Anke Schr?der,Melanie Schlüter,Maurice Illisuch model, the Segment Anything Model (SAM), a prompt-driven segmentation model, has shown remarkable performance improvements, surpassing state-of-the-art approaches in medical image segmentation. However, existing methods primarily rely on tuning strategies that require extensive data or prior pr

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978-3-031-45856-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/282480.jpg

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Domain Adaptation and Representation Transfer978-3-031-45857-6Series ISSN 0302-9743 Series E-ISSN 1611-3349