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Document Information Extraction
Janík, Roman ; Špaňhel, Jakub (oponent) ; Hradiš, Michal (vedoucí práce)
With development of digitization comes the need for historical document analysis. Named Entity Recognition is an important task for Information extraction and Data mining. The goal of this thesis is to develop a system for extraction of information from Czech historical documents, such as newspapers, chronicles and registry books. An information extraction system was designed, the input of which is scanned historical documents processed by the OCR algorithm. The system is based on a modified RoBERTa model. The extraction of information from Czech historical documents brings challenges in the form of the need for a suitable corpus for historical Czech. The corpora Czech Named Entity Corpus (CNEC) and Czech Historical Named Entity Corpus (CHNEC) were used to train the system, together with my own created corpus. The system achieves 88.85 F1 score on CNEC and 87.19 F1 score on CHNEC, obtaining new state-of-the-art results.
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Deep Neural Networks for Historical Document Classification
Pinkeová, Bettina ; Kohút, Jan (oponent) ; Kišš, Martin (vedoucí práce)
The aim of this work is to create a system for historical documents classification . The task is specifically about classification of documents according to the place of origin. Several systems are proposed for solving this problem, in the work. The first designed and implemented system is based on a convolutional neural network with a self-attention mechanism instead of an average pooling layer. Another system is based on the BEiT model, which is built on a visual transformer. The BEiT model was pretrained on the task of masked image modelling and subsequently trained on the given classification task. The system based on convolutional neural network achieved an accuracy of 81.6% and the system based on masked image modelling achieved an accuracy of 82.9%. The systems implemented in this work, surpassed the systems participating in the ICDAR 2021 conference in terms of success.
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