Abstract
In the past 4 years Deep Learning (DL) has re-entered the computer vision scene dramatically, by completely shifting the design paradigm compared to the last 20 years. Whereas before the error rates in image analysis were more or less stagnant, since 2012 DL kept halving them each year, in some recent cases even achieving super-human performance! All typical tasks such classification, detection and segmentation benefited across all related applications such as traffic sign recognition, natural image analysis, automatic captioning. These developments move computer vision from a scientific playground to a productizable technology.
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© 2016 Springer-Verlag Berlin Heidelberg
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Bordag, S. (2016). Significant Advances in Medical Image Analysisorem. In: Tolxdorff, T., Deserno, T., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2016. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49465-3_1
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DOI: https://doi.org/10.1007/978-3-662-49465-3_1
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-49464-6
Online ISBN: 978-3-662-49465-3
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