Title: Optimization of the energy consumption of a building with PV
Authors: Jiřinec, Jakub
Rot, David
Jiřinec, Stanislav
Citation: MARTÍNEK, J., LENC, L., KRÁL, P. Training Strategies for OCR Systems for Historical Documents. In: Artificial Intelligence Applications and Innovation. Cham: Springer, 2019. s. 362-373. ISBN 978-3-030-19822-0, ISSN 1868-4238.
Issue Date: 2019
Publisher: Springer
Document type: konferenční příspěvek
URI: 2-s2.0-85065915057
ISBN: 978-3-030-19822-0
Keywords in different language: optimization;energy consuption;photovoltaic system (PV);measuring system;regulation system;programmable logic controller (PLC);heat pump
Abstract in different language: This paper presents an overview of training strategies for optical character recognition of historical documents. The main issue is the lack of the annotated data and its quality. We summarize several ways of synthetic data preparation. The main goal of this paper is to show and compare possibilities how to train a convolutional recurrent neural network classifier using the synthetic data and its combination with a real annotated dataset.
Rights: Plný text je přístupný v rámci univerzity přihlášeným uživatelům.
© Springer
Appears in Collections:Konferenční příspěvky / Conference papers (NTIS)
Konferenční příspěvky / Conference Papers (KIV)

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/35864

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