Impact of the ground truth quality for handwriting recognition
Michael Jungo,
Lars Vögtlin,
Atefeh Fakhari
et al.
Abstract:Handwriting recognition is a key technology for accessing the content of old manuscripts, helping to preserve cultural heritage. Deep learning shows an impressive performance in solving this task. However, to achieve its full potential, it requires a large amount of labeled data, which is difficult to obtain for ancient languages and scripts. Often, a trade-off has to be made between ground truth quantity and quality, as is the case for the recently introduced Bullinger database. It contains an impressive amou… Show more
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