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Research on application framework of electronic document business based on big data technology
With the rapid development of big data technology, electronic documents are more and more widely used. Aiming at the characteristics of large amount...
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Design of an academic document forgery detection system
Advances in digital technology and communication are reducing the popularity of physical or paper-based documents, particularly in the official...
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The YOLO model that still excels in document layout analysis
Document layout analysis can help people better understand and use the information in a document. However, the diversity of document layouts and...
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Doc-Attentive-GAN: attentive GAN for historical document denoising
Image denoising attempts to restore images that have been degraded. Historical document denoising is specially challenging because there is...
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Can document characteristics affect motivations for literature usage?
Beyond citations, the impact of scientific publications is often measured by usage metrics, such as downloads, save counts and sharing counts....
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Exploring AI-driven approaches for unstructured document analysis and future horizons
In the current industrial landscape, a significant number of sectors are grappling with the challenges posed by unstructured data, which incurs...
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A semi-supervised framework for concept-based hierarchical document clustering
Text clustering is used in various applications of text analysis. In the clustering process, the employed document representation method has a...
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Enhanced Named Entity Recognition algorithm for financial document verification
Many enterprise systems are document-intensive and require extensive manual verification. The verification process has challenge in terms of time and...
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Loss Function for Training Models of Segmentation of Document Images
AbstractThis work is devoted to improving the quality of segmentation of images of various scientific papers and legal acts by neural network models...
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DocXclassifier: towards a robust and interpretable deep neural network for document image classification
Model interpretability and robustness are becoming increasingly critical today for the safe and practical deployment of deep learning (DL) models in...
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A systematic review on handwritten document analysis and recognition
Document Analysis and Recognition (DAR) is ongoing research that has been studied extensively for many decades and it has achieved a substantial...
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Document Image Binarization
Documents often get affected by noise due to various issues like casual handling occurred during storing, or image acquisition processes. These...
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Document Image Analysis Using Deep Multi-modular Features
Texture or repeating patterns, discriminative patches, and shapes are the salient features for various document image analysis problems. This article...
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A document image classification system fusing deep and machine learning models
Artificial Intelligence (AI) technologies are now widely employed to overcome human-induced faults in a variety of systems used in our daily lives,...
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Knowledge Management for Document Management
Chapter Goal: Demonstrate how Microsoft technologies can streamline document management processes to enhance knowledge management.
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RefCit2vec: embedding models considering references and citations for measuring document similarity
This study outlines the intellectual structure of Library and Information Science in terms of the venues with RefCit2vec, an embedding method...
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Analysis of Document Security Features
Document fraud has been rising for several years, severely impacting individuals, organizations and governments. Security features in documents...
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Document Region Classification
After region segmentation, it is necessary to identify the functional labels of the segmented regions. This is because OCR engines can only consider...
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Multimodal End-to-End Visual Document Parsing
The record meterials used in some industries including medical service and insurance, whose information has high commercial and scientific research...
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Hybrid medical named entity recognition using document structure and surrounding context
Nowadays, there is a huge amount of electronic medical documents created in natural language by medical specialists, containing useful information...
