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Found 12 papers, 4 papers with code
Exploring Multiple Strategies to Improve Multilingual Coreference Resolution in CorefUD
The proposed model is based on the standard end-to-end neural coreference resolution system.
Well-calibrated Confidence Measures for Multi-label Text Classification with a Large Number of Labels
We present experimental results using the original and the proposed efficient LP-ICP on two English and one Czech language data-sets.
Linear Transformations for Cross-lingual Sentiment Analysis
This paper deals with cross-lingual sentiment analysis in Czech, English and French languages.
ICDAR 2021 Competition on Historical Map Segmentation
Task~2 consists in segmenting map content from the larger map sheet, and was won by the UWB team using a U-Net-like FCN combined with a binarization method to increase detection edge accuracy.
Re-ranking for Writer Identification and Writer Retrieval
We show that a re-ranking step based on k-reciprocal nearest neighbor relationships is advantageous for writer identification, even if only a few samples per writer are available.
Cross-lingual Approaches for Task-specific Dialogue Act Recognition
In this paper we exploit cross-lingual models to enable dialogue act recognition for specific tasks with a small number of annotations.
Deep Generalized Max Pooling
Global pooling layers are an essential part of Convolutional Neural Networks (CNN).
Multi-lingual Dialogue Act Recognition with Deep Learning Methods
Two multi-lingual models are proposed for this task.
Czech Text Document Corpus v 2.0
This paper introduces "Czech Text Document Corpus v 2. 0", a collection of text documents for automatic document classification in Czech language.
Enhanced Local Binary Patterns for Automatic Face Recognition
This descriptor considers a local neighbourhood of a pixel to compute the feature vector values.
Deep Neural Networks for Czech Multi-label Document Classification
This paper is focused on automatic multi-label document classification of Czech text documents.
Unsupervised Dialogue Act Induction using Gaussian Mixtures
This paper introduces a new unsupervised approach for dialogue act induction.
