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What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels [PDF]
Computer Vision and Pattern Recognition, 2021 Scene text recognition (STR) task has a common practice: All state-of-the-art STR models are trained on large synthetic data. In contrast to this practice, training STR models only on fewer real labels (STR with fewer labels) is important when we have to
Jeonghun Baek, Yusuke Matsui, K. Aizawa
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Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition [PDF]
European Conference on Computer Vision, 2022 . Artistic text recognition is an extremely challenging task with a wide range of applications. However, current scene text recognition methods mainly focus on irregular text while have not explored artistic text specifically.
Xudong Xie +4 more
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A Benchmark of Parsing Vietnamese Publications
IEEE Access, 2022 In recent decades, digital transformation has received growing attention worldwide, that has leveraged the explosion of digitized document data. In this paper, we address the problem of parsing publications, in particular, Vietnamese publications.
Khang Nguyen +5 more
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Robust Sewer Defect Detection With Text Analysis Based on Deep Learning
IEEE Access, 2022 Sewerage systems play a vital role in building modern cities, providing appropriate ways to release liquid wastes. Due to the rapid expansion of cities, the deterioration of sewage pipes are increasing.
Chanmi Oh +3 more
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Towards Accurate Scene Text Recognition With Semantic Reasoning Networks [PDF]
Computer Vision and Pattern Recognition, 2020 Scene text image contains two levels of contents: visual texture and semantic information. Although the previous scene text recognition methods have made great progress over the past few years, the research on mining semantic information to assist text ...
Deli Yu +5 more
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IEEE Access, 2023 Many existing text recognition methods rely on the structure of Latin characters and words. Such methods may not be able to deal with non-Latin scripts that have highly complex features, such as character stacking, diacritics, ligatures, non-uniform ...
Rina Buoy +3 more
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MaskOCR: Text Recognition with Masked Encoder-Decoder Pretraining [PDF]
arXiv.org, 2022 Text images contain both visual and linguistic information. However, existing pre-training techniques for text recognition mainly focus on either visual representation learning or linguistic knowledge learning.
Pengyuan Lyu +9 more
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IEEE Access, 2020 The adoption of electronic health records (EHRs) is an important step in the development of modern medicine. However, complete health records are not often available during treatment because of the functional problem of the EHR system or information ...
Wenyuan Xue, Qingyong Li, Qiyuan Xue
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Applied Sciences, 2023 Existing methods for monitoring internet public opinion rely primarily on regular crawling of textual information on web pages but cannot quickly and accurately acquire and identify textual information in images and videos and discriminate sentiment. The
Xing Liu +8 more
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Primitive Representation Learning for Scene Text Recognition [PDF]
Computer Vision and Pattern Recognition, 2021 Scene text recognition is a challenging task due to di-verse variations of text instances in natural scene images. Conventional methods based on CNN-RNN-CTC or encoder-decoder with attention mechanism may not fully investigate stable and efficient ...
Ruijie Yan +3 more
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