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Paperback. Condition: new. Paperback. Multilingual text recognition is crucial for cross language information acquisition and related applications in the mobile computing era. The core problem is to find efficient representation and decoding methods for multilingual text recognition, including scene text recognition or handwriting recognition tasks.This book introduces a novel deep learning framework termed Primitive Representation Learning for sequence modeling. In contrast to conventional approaches that employ either (1) convolutional neural networks (CNNs) combined with recurrent neural networks (RNNs) and connectionist temporal classification (CTC) for decoding, or (2) attention-based encoder-decoder architectures, the proposed framework offers an alternative paradigm for sequence representation and processing. Primitive representations are learned via global feature aggregation and then transformed into high level visual text representations via a graph convolutional network, which enables parallel decoding for text transcription. Multielement attention mechanism and temporal residual mechanism are further introduced to enhance the utilization of spatial and temporal feature information.The methods presented in this book have been evaluated on public datasets and applied to scene text recognition and handwriting recognition systems. Readers will gain a better understanding of state of the art methods and research findings in multilingual scene text recognition, handwriting recognition, and related fields. The prerequisites needed to understand this book include basic knowledge for machine learning and deep learning. The core problem is to find efficient representation and decoding methods for multilingual text recognition, including scene text recognition or handwriting recognition tasks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Multilingual text recognition is crucial for cross language information acquisition and related applications in the mobile computing era. The core problem is to find efficient representation and decoding methods for multilingual text recognition, including scene text recognition or handwriting recognition tasks.This book introduces a novel deep learning framework termed Primitive Representation Learning for sequence modeling. In contrast to conventional approaches that employ either (1) convolutional neural networks (CNNs) combined with recurrent neural networks (RNNs) and connectionist temporal classification (CTC) for decoding, or (2) attention-based encoder-decoder architectures, the proposed framework offers an alternative paradigm for sequence representation and processing. Primitive representations are learned via global feature aggregation and then transformed into high level visual text representations via a graph convolutional network, which enables parallel decoding for text transcription. Multielement attention mechanism and temporal residual mechanism are further introduced to enhance the utilization of spatial and temporal feature information.The methods presented in this book have been evaluated on public datasets and applied to scene text recognition and handwriting recognition systems. Readers will gain a better understanding of state of the art methods and research findings in multilingual scene text recognition, handwriting recognition, and related fields. The prerequisites needed to understand this book include basic knowledge for machine learning and deep learning.
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Taschenbuch. Condition: Neu. Multilingual Text Recognition | A Deep Learning Approach | Liangrui Peng (u. a.) | Taschenbuch | xiii | Englisch | 2026 | Springer | EAN 9789819678976 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Document Analysis and Recognition - ICDAR 2024 | 18th International Conference, Athens, Greece, August 30-September 4, 2024, Proceedings, Part VI | Elisa H. Barney Smith (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvii | Englisch | 2024 | Springer | EAN 9783031705519 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30-September 4, 2024.The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions.The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.
Taschenbuch. Condition: Neu. Document Analysis and Recognition - ICDAR 2024 | 18th International Conference, Athens, Greece, August 30 - September 4, 2024, Proceedings, Part III | Elisa H. Barney Smith (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvii | Englisch | 2024 | Springer | EAN 9783031705427 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Condition: Neu. Document Analysis and Recognition - ICDAR 2024 | 18th International Conference, Athens, Greece, August 30-September 4, 2024, Proceedings, Part IV | Elisa H. Barney Smith (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvii | Englisch | 2024 | Springer | EAN 9783031705458 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Condition: Neu. Document Analysis and Recognition - ICDAR 2024 | 18th International Conference, Athens, Greece, August 30-September 4, 2024, Proceedings, Part V | Elisa H. Barney Smith (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvii | Englisch | 2024 | Springer | EAN 9783031705489 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Condition: Neu. Document Analysis and Recognition - ICDAR 2024 | 18th International Conference, Athens, Greece, August 30-September 4, 2024, Proceedings, Part I | Elisa H. Barney Smith (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvii | Englisch | 2024 | Springer | EAN 9783031705328 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30-September 4, 2024.The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions.The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more.