Papers by Ladislav Lenc

2 papers
Czech Text Document Corpus v 2.0 (L18-1)

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Challenge: a corpus of text documents for automatic document classification in Czech is presented . paper aims to facilitate a straightforward comparison of document classification approaches on Czech data .
Approach: This paper introduces a collection of text documents for automatic document classification in Czech language.
Outcome: The proposed corpus is based on the Czech news agency's real newspaper articles . it is used for evaluation of multi-label document classification approaches .
COMICORDA: Dialogue Act Recognition in Comic Books (2024.lrec-main)

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Challenge: Existing work on dialogue act recognition from images is limited to speech balloon segmentation and optical character recognition.
Approach: They propose a novel DA recognition approach for comic books using speech balloon segmentation, optical character recognition and DA classification.
Outcome: The proposed method achieves 98% average precision for speech balloon segmentation and exceeds 70% accuracy for the DA recognition task.

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