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Titlebook: Open-Set Text Recognition; Concepts, Framework, Xu-Cheng Yin,Chun Yang,Chang Liu Book 2024 The Editor(s) (if applicable) and The Author(s),

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Open-Set Text Recognition978-981-97-0361-6Series ISSN 2191-5768 Series E-ISSN 2191-5776
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Xu-Cheng Yin,Chun Yang,Chang Liuts (Chalopin & Gonçalves, SODA 2009), .-shapes (Gonçalves .., SODA 2018). For general graphs, however, even deciding whether such representations exist is often .-hard. We consider apex graphs, ...., graphs that can be made planar by removing one vertex from them. We show, somewhat surprisingly, tha
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Xu-Cheng Yin,Chun Yang,Chang Liuts (Chalopin & Gonçalves, SODA 2009), .-shapes (Gonçalves .., SODA 2018). For general graphs, however, even deciding whether such representations exist is often .-hard. We consider apex graphs, ...., graphs that can be made planar by removing one vertex from them. We show, somewhat surprisingly, tha
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Background,conventional OCR methods, and their applications. First, we introduce the concept of open-set (or open-world). We discuss the different usage of open-set from various research areas and declare the OSTR task concern on either identification or recognition capability, with both seen and novel (abnorm
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Open-Set Text Recognition: Concept, Dataset, Protocol, and Framework,sk and the relation between OSTR and other tasks. Secondly, we narrow down to the specific protocols used to measure model performances on the task. Before reaching the specific protocol, we introduce the commonly used protocols and datasets to lay out the background. Finally, this chapter presents
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