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Published in:
2022 | OriginalPaper | Chapter
Abstract: Task Fingerprinting for Meta Learning in Biomedical Image Analysis
Authors : Patrick Godau, Lena Maier-Hein
Published in: Bildverarbeitung für die Medizin 2022
Publisher: Springer Fachmedien Wiesbaden
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Shortage of annotated data is one of the greatest bottlenecks related to biomedical image analysis in general, and surgical data science (SDS) in particular. Meta learning studies howlearning systems can increase in efficiency through experience and could thus evolve as an important concept to overcome data sparsity. A core capability of meta learningbased approaches is the identification of similar previous tasks given a new task. We recently addressed this problem and presented the concept of task fingerprinting [1], which involves representing a task (comprising images and labels), by a vector of fixed length irrespective of data set size, types of labels or specific resolutions (Fig. 1).