Your talks are welcome! Please don't hesitate to get in touch if you have a topic you'd like to talk about or a project you want to present! -> [masked] :)
Anyline is going to sponsor free drinks at the beginning of the evening.
7pm: Grab a welcome drink
7.30pm: Is the Singularity near?
Where technology and AI could lead us: Facts, forecasts and disruptive projections.
A talk by Marcus Oppitz.
8.15pm: Baseline Detection in Historical Documents using Convolutional U-Nets.
Presented at the 13th IAPR International Workshop on Document Analysis Systems in Vienna.
A talk by Michael Sprinzl
Baseline detection is still a challenging task for heterogeneous collections of historical documents. We present a novel approach to baseline extraction in such settings, turning out the winning entry to the ICDAR 2017 Competition on Baseline detection (cBAD). It utilizes deep convolutional nets (CNNs) for both, the actual extraction of baselines, as well as for a simple form of layout analysis in a pre-processing step. To the best of our knowledge it is the first CNN-based system for baseline extraction applying a U-net architecture and sliding window detection, profiting from a high local accuracy of the candidate lines extracted.
Final baseline post-processing complements our approach, compensating for inaccuracies mainly due to missing context
information during sliding window detection. We experimentally evaluate the components of our system individually on
the cBAD dataset. Moreover, we investigate how it generalizes to different data by means of the dataset used for the baseline
extraction task of the ICDAR 2017 Competition on Layout Analysis for Challenging Medieval Manuscripts (HisDoc). A comparison with the results reported for HisDoc shows that it also outperforms the contestants of the latter.
See you soon!