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Graph-based Keyword Spotting

Graph-based Keyword Spotting PDF Author: Stauffer Michael
Publisher: World Scientific
ISBN: 9811206643
Category : Computers
Languages : en
Pages : 296

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Book Description
Keyword Spotting (KWS) has been proposed as a flexible and more error-tolerant alternative to full transcriptions. In most cases, it allows to retrieve arbitrary query words in handwritten historical document.This comprehensive compendium gives a self-contained preamble and visually attractive description to the field of graph-based KWS. The volume highlights a profound insight into each step of the whole KWS pipeline, viz. image preprocessing, graph representation and graph matching.Written by two world-renowned co-authors, this unique title combines two very current research fields of graph-based pattern recognition and document analysis. The book serves as an attractive teaching material for graduate students, as well as a useful reference text for professionals, academics and researchers.

Graph-based Keyword Spotting

Graph-based Keyword Spotting PDF Author: Stauffer Michael
Publisher: World Scientific
ISBN: 9811206643
Category : Computers
Languages : en
Pages : 296

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Book Description
Keyword Spotting (KWS) has been proposed as a flexible and more error-tolerant alternative to full transcriptions. In most cases, it allows to retrieve arbitrary query words in handwritten historical document.This comprehensive compendium gives a self-contained preamble and visually attractive description to the field of graph-based KWS. The volume highlights a profound insight into each step of the whole KWS pipeline, viz. image preprocessing, graph representation and graph matching.Written by two world-renowned co-authors, this unique title combines two very current research fields of graph-based pattern recognition and document analysis. The book serves as an attractive teaching material for graduate students, as well as a useful reference text for professionals, academics and researchers.

Graph-based Keyword Spotting

Graph-based Keyword Spotting PDF Author: Michael Stauffer
Publisher:
ISBN: 9789811206634
Category : Document imaging systems
Languages : en
Pages : 297

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Book Description
Keyword Spotting (KWS) has been proposed as a flexible and more error-tolerant alternative to full transcriptions. In most cases, it allows to retrieve arbitrary query words in handwritten historical document. This comprehensive compendium gives a self-contained preamble and visually attractive description to the field of graph-based KWS. The volume highlights a profound insight into each step of the whole KWS pipeline, viz. image preprocessing, graph representation and graph matching. Written by two world-renowned co-authors, this unique title combines two very current research fields of graph-based pattern recognition and document analysis. The book serves as an attractive teaching material for graduate students, as well as a useful reference text for professionals, academics and researchers.

Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition PDF Author: Donatello Conte
Publisher: Springer
ISBN: 3030200817
Category : Computers
Languages : en
Pages : 247

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Book Description
This book constitutes the refereed proceedings of the 12th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2019, held in Tours, France, in June 2019. The 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. The papers discuss research results and applications at the intersection of pattern recognition, image analysis, and graph theory. They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.

Graph-Based Representations in Pattern Recognition

Graph-Based Representations in Pattern Recognition PDF Author: Pasquale Foggia
Publisher: Springer
ISBN: 331958961X
Category : Computers
Languages : en
Pages : 289

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Book Description
This book constitutes the refereed proceedings of the 11th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2017, held in Anacapri, Italy, in May 2017. The 25 full papers and 2 abstracts of invited papers presented in this volume were carefully reviewed and selected from 31 submissions. The papers discuss research results and applications in the intersection of pattern recognition, image analysis, graph theory, and also the application of graphs to pattern recognition problems in other fields like computational topology, graphic recognition systems and bioinformatics.

Business Information Systems and Technology 4.0

Business Information Systems and Technology 4.0 PDF Author: Rolf Dornberger
Publisher: Springer
ISBN: 3319743228
Category : Technology & Engineering
Languages : en
Pages : 288

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Book Description
This book discusses digitalization trends and their concrete applications in business and societal contexts. It summarizes new findings from research, teaching and management activities comprising digital transformation, e-business, the representation of knowledge, human–computer interaction and business optimization. The trends discussed include artificial intelligence, virtual reality, robotics, blockchain, and many more. Professors and researchers who conduct research and teach at the interface between academia and business present the latest advances in their field. The book adopts the philosophy of applied sciences and combines both rigorous research and practical applications. As such, it addresses the needs of both professors and researchers, who are constantly seeking inspiration, and of managers seeking to tap the potential of the latest trends to take their business to the next level. Readers will find answers to pressing questions that arise in their daily work.

Digital Heritage

Digital Heritage PDF Author: Marinos Ioannides
Publisher: Springer
ISBN: 331913695X
Category : Computers
Languages : en
Pages : 832

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Book Description
This book constitutes the refereed proceedings of the 5th International Conference on Digital Heritage, EuroMed 2014, held in Limassol, Cyprus, in November 2014. The 84 full and 51 short papers presented were carefully reviewed and selected from 438 submissions. They focus on the interdisciplinary and multi-disciplinary research concerning cutting edge cultural heritage informatics, -physics, chemistry and engineering and the use of technology for the representation, documentation, archiving, protection, preservation and communication of Cultural Heritage knowledge.

Structural, Syntactic, and Statistical Pattern Recognition

Structural, Syntactic, and Statistical Pattern Recognition PDF Author: Antonio Robles-Kelly
Publisher: Springer
ISBN: 3319490559
Category : Computers
Languages : en
Pages : 588

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Book Description
This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition, S+SSPR 2016, consisting of the International Workshop on Structural and Syntactic Pattern Recognition SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The 51 full papers presented were carefully reviewed and selected from 68 submissions. They are organized in the following topical sections: dimensionality reduction, manifold learning and embedding methods; dissimilarity representations; graph-theoretic methods; model selection, classification and clustering; semi and fully supervised learning methods; shape analysis; spatio-temporal pattern recognition; structural matching; text and document analysis.

Spotting Keywords in Offline Handwritten Documents Using Hausdorff Edit Distance

Spotting Keywords in Offline Handwritten Documents Using Hausdorff Edit Distance PDF Author: Mohammad Reza Ameri
Publisher:
ISBN:
Category :
Languages : en
Pages : 166

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Book Description
Keyword spotting has become a crucial topic in handwritten document recognition, by enabling content-based retrieval of scanned documents using search terms. With a query keyword, one can search and index the digitized handwriting which in turn facilitates understanding of manuscripts. Common automated techniques address the keyword spotting problem through statistical representations. Structural representations such as graphs apprehend the complex structure of handwriting. However, they are rarely used, particularly for keyword spotting techniques, due to high computational costs. The graph edit distance, a powerful and versatile method for matching any type of labeled graph, has exponential time complexity to calculate the similarities of graphs. Hence, the use of graph edit distance is constrained to small size graphs. The recently developed Hausdorff edit distance algorithm approximates the graph edit distance with quadratic time complexity by efficiently matching local substructures. This dissertation speculates using Hausdorff edit distance could be a promising alternative to other template-based keyword spotting approaches in term of computational time and accuracy. Accordingly, the core contribution of this thesis is investigation and development of a graph-based keyword spotting technique based on the Hausdorff edit distance algorithm. The high representational power of graphs combined with the efficiency of the Hausdorff edit distance for graph matching achieves remarkable speedup as well as accuracy. In a comprehensive experimental evaluation, we demonstrate the solid performance of the proposed graph-based method when compared with state of the art, both, concerning precision and speed. The second contribution of this thesis is a keyword spotting technique which incorporates dynamic time warping and Hausdorff edit distance approaches. The structural representation of graph-based approach combined with statistical geometric features representation compliments each other in order to provide a more accurate system. The proposed system has been extensively evaluated with four types of handwriting graphs and geometric features vectors on benchmark datasets. The experiments demonstrate a performance boost in which outperforms individual systems.

Handwritten Historical Document Analysis, Recognition, And Retrieval - State Of The Art And Future Trends

Handwritten Historical Document Analysis, Recognition, And Retrieval - State Of The Art And Future Trends PDF Author: Andreas Fischer
Publisher: World Scientific
ISBN: 9811203253
Category : Computers
Languages : en
Pages : 268

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Book Description
In recent years, libraries and archives all around the world have increased their efforts to digitize historical manuscripts. To integrate the manuscripts into digital libraries, pattern recognition and machine learning methods are needed to extract and index the contents of the scanned images.The unique compendium describes the outcome of the HisDoc research project, a pioneering attempt to study the whole processing chain of layout analysis, handwriting recognition, and retrieval of historical manuscripts. This description is complemented with an overview of other related research projects, in order to convey the current state of the art in the field and outline future trends.This must-have volume is a relevant reference work for librarians, archivists and computer scientists.

Document Analysis and Recognition – ICDAR 2021

Document Analysis and Recognition – ICDAR 2021 PDF Author: Josep Lladós
Publisher: Springer Nature
ISBN: 3030865495
Category : Computers
Languages : en
Pages : 650

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Book Description
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports. The papers are organized into the following topical sections: historical document analysis, document analysis systems, handwriting recognition, scene text detection and recognition, document image processing, natural language processing (NLP) for document understanding, and graphics, diagram and math recognition.