cBAD: ICDAR2017 Competition on Baseline Detection
| Autor: | Florian Kleber, Basilis Gatos, Markus Diem, Stefan Fiel, Tobias Grüning |
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| Rok vydání: | 2017 |
| Předmět: |
Measure (data warehouse)
Modality (human–computer interaction) business.industry Computer science 02 engineering and technology Image segmentation cBAD Handwriting segmentation Machine learning computer.software_genre 01 natural sciences baseline detection Test (assessment) text-line detection 010309 optics Competition (economics) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Baseline (configuration management) computer |
| Zdroj: | ICDAR 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR) reposiTUm OpenAIRE |
| DOI: | 10.1109/icdar.2017.222 |
| Popis: | The cBAD competition aims at benchmarking state-of-the-art baseline detection algorithms. It is in line with previous competitions such as the ICDAR 2013 Handwriting Segmentation Contest. A new, challenging, dataset was created to test the behavior of state-of-the-art systems on real world data. Since traditional evaluation schemes are not applicable to the size and modality of this dataset, we present a new one that introduces baselines to measure performance. We received submissions from five different teams. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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