Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Liao, Minghui"'
Publikováno v:
Science China Information Sciences. 65
Ethiopic/Amharic script is one of the oldest African writing systems, which serves at least 23 languages (e.g., Amharic, Tigrinya) in East Africa for more than 120 million people. The Amharic writing system, Abugida, has 282 syllables, 15 punctuation
Recent end-to-end trainable methods for scene text spotting, integrating detection and recognition, showed much progress. However, most of the current arbitrary-shape scene text spotters use region proposal networks (RPN) to produce proposals. RPN re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7118ec8d1a410aeacd9bb56774d92809
http://arxiv.org/abs/2007.09482
http://arxiv.org/abs/2007.09482
Scene text detection, which is one of the most popular topics in both academia and industry, can achieve remarkable performance with sufficient training data. However, the annotation costs of scene text detection are huge with traditional labeling me
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11becce18a694baa437e14d85d83cebe
Autor:
Liu, Xi, Zhang, Rui, Zhou, Yongsheng, Jiang, Qianyi, Song, Qi, Li, Nan, Zhou, Kai, Wang, Lei, Wang, Dong, Liao, Minghui, Yang, Mingkun, Bai, Xiang, Shi, Baoguang, Karatzas, Dimosthenis, Lu, Shijian, Jawahar, C. V.
Chinese scene text reading is one of the most challenging problems in computer vision and has attracted great interest. Different from English text, Chinese has more than 6000 commonly used characters and Chinesecharacters can be arranged in various
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2300c1fa71c51be3accbb4651129921a
Recently, models based on deep neural networks have dominated the fields of scene text detection and recognition. In this paper, we investigate the problem of scene text spotting, which aims at simultaneous text detection and recognition in natural i
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e87c6eeb0bbfd2bfa89376dcc2cc782