Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Yulia S. Chernyshova"'
Publikováno v:
IEEE Access, Vol 8, Pp 32587-32600 (2020)
In this paper, we introduce an “on the device” text line recognition framework that is designed for mobile or embedded systems. We consider per-character segmentation as a language-independent problem and individual character recognition as a lan
Externí odkaz:
https://doaj.org/article/7f00eb4721a74dd09b228096484c78d3
Publikováno v:
IEEE Access, Vol 8, Pp 32587-32600 (2020)
In this paper, we introduce an “on the device” text line recognition framework that is designed for mobile or embedded systems. We consider per-character segmentation as a language-independent problem and individual character recognition as a lan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0de171d1b928a1e3468fbe9899cf4a56
https://ieeexplore.ieee.org/document/8999509/
https://ieeexplore.ieee.org/document/8999509/
Publikováno v:
Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030863302
ICDAR (2)
ICDAR (2)
In this paper, we present a new dataset for identity documents (IDs) recognition called MIDV-LAIT. The main feature of the dataset is the textual fields in Perso-Arabic, Thai, and Indian scripts. Since open datasets with real IDs may not be published
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba681b065208d877a575056d760738a1
https://doi.org/10.1007/978-3-030-86331-9_17
https://doi.org/10.1007/978-3-030-86331-9_17
Publikováno v:
ICMV
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6882f0aed562a7231b6a0d4d351a56a6
https://doi.org/10.1117/12.2559449
https://doi.org/10.1117/12.2559449
Publikováno v:
ICMV
In this paper we study the real-time augmentation - method of increasing variability of training dataset during the learning process. We consider the most common label-preserving deformations, which can be useful in many practical tasks. Due to limit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8cafa4c0e0453a519a6c6c4af039796
https://doi.org/10.1117/12.2522969
https://doi.org/10.1117/12.2522969
Publikováno v:
ICMV
This paper addresses one of the fundamental problems of machine learning - training data acquiring. Obtaining enough natural training data is rather difficult and expensive. In last years usage of synthetic images has become more beneficial as it all
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a4c337832298ce05c49825e704b6abc
https://doi.org/10.1117/12.2310119
https://doi.org/10.1117/12.2310119
Publikováno v:
ICMV
In this paper, we consider the problem of detecting counterfeit identity documents in images captured with smartphones. As the number of documents contain special fonts, we study the applicability of convolutional neural networks (CNNs) for detection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cc26af6183d8e68c4cf6a0fb1d1acf5
Publikováno v:
Pattern Recognition & Image Analysis; Dec2023, Vol. 33 Issue 4, p730-742, 13p