Open-Set Text Recognition Concepts, Framework, and Algorithms
In real-world applications, new data, patterns, and categories that were not covered by the training data can frequently emerge, necessitating the capability to detect and adapt to novel characters incrementally. Researchers refer to these challenges as the Open-Set Text Recognition (OSTR) task, whi...
Main Authors: | , , |
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Format: | eBook |
Language: | English |
Published: |
Singapore
Springer Nature Singapore
2024, 2024
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Edition: | 1st ed. 2024 |
Series: | SpringerBriefs in Computer Science
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Introduction
- Background
- Open-Set Text Recognition: Concept, DataSet, Protocol, and Framework
- Open-Set Text Recognition Implementations(I): Label-to-Representation Mapping
- Open-Set Text Recognition Implementations(II): Sample-to-Representation Mapping
- Open-Set Text Recognition Implementations(III): Open-set Predictor
- Open Set Text Recognition: Case-studies
- Discussions and Future Directions.