Open-Set Text Recognition: Concepts, Framework, and Algorithms

Yin, Xu-Cheng, Yang, Chun, Liu, Chang

Open-Set Text Recognition: Concepts, Framework, and Algorithms
  • 出版商: Springer
  • 出版日期: 2024-04-02
  • 售價: $2,200
  • 貴賓價: 9.5 折 $2,090
  • 語言: 英文
  • 頁數: 121
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9819703603
  • ISBN-13: 9789819703609
  • 相關分類: Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

商品描述

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, which has, in recent years, emerged as one of the prominent issues in the field of text recognition. This book begins by providing an introduction to the background of the OSTR task, covering essential aspects such as open-set identification and recognition, conventional OCR methods, and their applications. Subsequently, the concept and definition of the OSTR task are presented encompassing its objectives, use cases, performance metrics, datasets, and protocols. A general framework for OSTR is then detailed, composed of four key components: The Aligned Represented Space, the Label-to-Representation Mapping, the Sample-to-Representation Mapping, and the Open-set Predictor. In addition, possible implementations of each module within the framework are discussed. Following this, two specific open-set text recognition methods, OSOCR and OpenCCD, are introduced. The book concludes by delving into applications and future directions of Open-set text recognition tasks.

This book presents a comprehensive overview of the open-set text recognition task, including concepts, framework, and algorithms. It is suitable for graduated students and young researchers who are majoring in pattern recognition and computer science, especially interdisciplinary research.

商品描述(中文翻譯)

在現實世界的應用中，常常會出現未被訓練數據涵蓋的新數據、模式和類別，這需要能夠增量地檢測和適應新字符的能力。研究人員將這些挑戰稱為開放式文本識別（OSTR）任務，近年來，它已成為文本識別領域中的一個重要問題之一。本書首先介紹了OSTR任務的背景，涵蓋了開放式識別和識別、傳統OCR方法及其應用等重要方面。隨後，介紹了OSTR任務的概念和定義，包括其目標、用例、性能指標、數據集和協議。然後，詳細介紹了OSTR的一般框架，包括四個關鍵組件：對齊表示空間、標籤到表示映射、樣本到表示映射和開放式預測器。此外，還討論了框架中每個模塊的可能實現方式。接下來，介紹了兩種特定的開放式文本識別方法：OSOCR和OpenCCD。本書最後深入探討了開放式文本識別任務的應用和未來發展方向。

本書全面介紹了開放式文本識別任務的概念、框架和算法。適合主修模式識別和計算機科學，尤其是跨學科研究的研究生和年輕研究人員閱讀。

作者簡介

Xu-Cheng Yin is a full professor, the director of Pattern Recognition and Artificial Intelligence Lab, Department of Computer Science and Technology, School of Computer and Communication Engineering, University of Science and Technology Beijing, China. He received the B.Sc. and M.Sc. degrees in computer science from the University of Science and Technology Beijing, China, in 1999 and 2002, respectively, and the Ph.D. degree in pattern recognition and intelligent systems from the Institute of Automation, Chinese Academy of Sciences, in 2006. He was a visiting professor in the College of Information and Computer Sciences, University of Massachusetts Amherst, USA, for three times (in 2013, 2014 and 2016). He recieved the National Science Fund for Distinguished Young Scholars in 2021. His research interests include pattern recognition, document analysis and recognition, computer vision, machine learning, and data mining.


Chun Yang received the B.Sc. and Ph.D. degrees in computer science from the

University of Science and Technology Beijing, China, in 2011 and 2018,

respectively. He is currently a lecturer with the School of Computer and

Communication Engineering, University of Science and Technology Beijing.


His current research interests include pattern

recognition, classifier ensemble, and document analysis and recognition.



Chang Liu received the B.Sc. degree in computer science from the University of

Science and Technology Beijing, China, in 2016, where he is currently pursuing

the Ph.D. degree with the Department of Computer Science and Technology.


His research interests include text detection,

few-shot learning, and text recognition.

作者簡介(中文翻譯)

尹旭成（Xu-Cheng Yin）是中國北京科技大學計算機與通信工程學院計算機科學與技術系模式識別與人工智能實驗室的全職教授和主任。他於1999年和2002年分別獲得北京科技大學計算機科學學士和碩士學位，並於2006年獲得中國科學院自動化研究所模式識別與智能系統博士學位。他曾三次擔任美國麻省大學阿默斯特分校信息與計算機科學學院的訪問教授（分別在2013年、2014年和2016年）。他於2021年獲得國家杰出青年科學基金。他的研究興趣包括模式識別、文件分析與識別、計算機視覺、機器學習和數據挖掘。

楊春（Chun Yang）於2011年和2018年分別獲得北京科技大學計算機科學學士和博士學位。他目前是北京科技大學計算機與通信工程學院的講師。他目前的研究興趣包括模式識別、分類器集成和文件分析與識別。

劉昶（Chang Liu）於2016年獲得北京科技大學計算機科學學士學位，目前正在該校計算機科學與技術系攻讀博士學位。他的研究興趣包括文本檢測、少樣本學習和文本識別。

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