Neural networks

Artificial neural networks are computing systems inspired by the biological neural networks that constitute animal brains. Such systems learn to do tasks by considering examples, generally without task-specific programming.

Publications

Jiří Martínek and Ladislav Lenc and Pavel Král
Building an efficient OCR system for historical documents with little training data
Neural Computing and Applications (2020)
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Neural networks
Jiří Martínek and Pavel Král and Ladislav Lenc and Christophe Cerisara
Multi-Lingual Dialogue Act Recognition with Deep Learning Methods
Interspeech 2019 (2019)
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Dialogue act recognition | Neural networks
Ladislav Lenc and Jiří Martínek and Pavel Král
Tools for Semi-automatic Preparation of Training Data for OCR
Artificial Intelligence Applications and Innovations (2019)
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Neural networks
Vincent Christlein and Anguelos Nicolaou and Pavel Král
Deep Generalized Max Pooling
15th International Conference on Document Analysis and Recognition (ICDAR 2019) (2019)
BibTex
Neural networks
Jiří Martínek and Ladislav Lenc and Pavel Král and Anguelos Nicolaou and Vincent Christlein
Hybrid Training Data for Historical Text OCR
15th International Conference on Document Analysis and Recognition (ICDAR 2019) (2019)
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Neural networks
Ladislav Lenc and Pavel Král
Deep Neural Networks for Czech Multi-label Document Classification
Computational Linguistics and Intelligent Text Processing (2018)
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Neural networks | Document classification
Jiří Martínek and Ladislav Lenc and Pavel Král
Neural networks for multi-lingual multi-label document classification
27th International Conference on Artificial Neural Networks (ICANN 2018) (2018)
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Neural networks | Document classification
Jiří Martínek and Ladislav Lenc and Pavel Král
Semantic Space Transformations for Cross-Lingual Document Classification
27th International Conference on Artificial Neural Networks (ICANN 2018) (2018)
BibTex | PDF
Semantic analysis | Neural networks | Document classification


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