to Document Analysis and Recognition.- Structure Extraction in Printed Documents Using Neural Approaches.- Machine Learning for Reading Order Detection in Document Image Understanding.- Decision-Based Specification and Comparison of Table Recognition Algorithms.- Machine Learning for Digital Document Processing: from Layout Analysis to Metadata Extraction.- Classification and Learning Methods for Character Recognition: Advances and Remaining Problems.- Combining Classifiers with Informational Confidence.- Self-Organizing Maps for Clustering in Document Image Analysis.- Adaptive and Interactive Approaches to Document Analysis.- Cursive Character Segmentation Using Neural Network Techniques.- Multiple Hypotheses Document Analysis.- Learning Matching Score Dependencies for Classifier Combination.- Perturbation Models for Generating Synthetic Training Data in Handwriting Recognition.- Review of Classifier Combination Methods.- Machine Learning for Signature Verification.- Off-line Writer Identification and Verification Using Gaussian Mixture Models.
Machine Learning in Document Analysis and Recognition
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to Document Analysis and Recognition.- Structure Extraction in Printed Documents Using Neural Approaches.- Machine Learning for Reading Order Detection in Document Image Understanding.- Decision-Based Specification and Comparison of Table Recognition Algorithms.- Machine Learning for Digital Document Processing: from Layout Analysis to Metadata Extraction.- Classification and Learning Methods for Character Recognition: Advances and Remaining Problems.- Combining Classifiers with Informational Confidence.- Self-Organizing Maps for Clustering in Document Image Analysis.- Adaptive and Interactive Approaches to Document Analysis.- Cursive Character Segmentation Using Neural Network Techniques.- Multiple Hypotheses Document Analysis.- Learning Matching Score Dependencies for Classifier Combination.- Perturbation Models for Generating Synthetic Training Data in Handwriting Recognition.- Review of Classifier Combination Methods.- Machine Learning for Signature Verification.- Off-line Writer Identification and Verification Using Gaussian Mixture Models.
1. This book constitutes the refereed proceedings of the 4th Workshop on Document Analysis and Recognition, DAR 2018, held in Conjunction with ICVGIP 2018, in Hyderabad, India,...
The compendium presents the latest results of the most prominent competitions held in the field of Document Analysis and Text Recognition. It includes a description of the participating systems and...
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,...
This six-volume set of LNCS 14187, 14188, 14189, 14190, 14191 and 14192 constitutes the refereed proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR...
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