Titlebook: Vorlesungen über Höhere Geometrie; Felix Klein,W. Blaschke (Professor der Mathematik) Textbook 1926Latest edition Springer-Verlag Berlin H

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Felix Klein imaging: (1) good initialization is more crucial for transformer-based models than for CNNs, (2) self-supervised learning based on masked image modeling captures more generalizable representations than supervised models, and (3) assembling a larger-scale domain-specific dataset can better bridge th

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an automatically identify discriminative locations in whole-brain MR images. The proposed AD.A framework consists of three key components: 1) a feature encoding module for representation learning of input MR images, 2) an attention discovery module for automatically locating dementia-related discrim

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Felix Kleinone representative visual benchmark after another. However, the competition between visual transformers and CNNs in medical imaging is rarely studied, leaving many important questions unanswered. As the first step, we benchmark how well existing transformer variants that use various (supervised and

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Felix Kleinalize as well to new patient cohorts, impeding their widespread adoption into real clinical contexts. One strategy to create a more diverse, generalizable training set is to naively pool datasets from different cohorts. Surprisingly, training on this . does not necessarily increase, and may even red

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