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Document Image Classification: Towards Assisting Visually Impaired
TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), 2019Our work aims to enable the visual information in a document to be accessible by the visually impaired or the blind people. The blind people prefer arts over science subjects in higher education because conveying equations and algorithms to them is seen as difficult. They should not be deprived of acquiring knowledge due to physical disabilities.
K. C. Shahira, A. Lijiya
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Utilizing image-based features in biomedical document classification
2015 IEEE International Conference on Image Processing (ICIP), 2015Images form a rich information source, which remains underutilized in biomedical document classification. We present here work that uses both image- and text-based features in order to identify articles of interest, in this case, pertaining to cis-regulatory modules in the context of gene-networks.
Kaidi Ma +9 more
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A functional classification approach to layout analysis of document images
Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93), 2002Layout analysis is both the segmentation and labeling of document images for automatic document input systems. The authors propose a layout analysis method based on a pattern classification scheme. They define the feature space in terms of low-level image processing features such as connected components and projection profiles.
Kazumi Iwane +2 more
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Segmentation and classification of mixed text/graphics/image documents
Pattern Recognition Letters, 1994Abstract In this paper, a feature-based document analysis system is presented which utilizes domain knowledge to segment and classify mixed text/graphics/image documents. In our approach, we first perform a run-length smearing operation followed by the stripe merging procedure to segment the blocks embedded in a document.
Kuo-Chin Fan, Chi-Hwa Liu, Yuan-Kai Wang
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Texture sparseness for pixel classification of business document images
International Journal on Document Analysis and Recognition (IJDAR), 2014Contemporary business documents contain diverse, multi-layered mixtures of textual, graphical, and pictorial elements. Existing methods for document segmentation and classification do not handle well the complexity and variety of contents, geometric layout, and elemental shapes.
Melissa Cote, Alexandra Branzan Albu
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Two Stream Deep Network for Document Image Classification
2019 International Conference on Document Analysis and Recognition (ICDAR), 2019This paper presents a novel two-stream approach for document image classification. The proposed approach leverages textual and visual modalities to classify document images into ten categories, including letter, memo, news article, etc. In order to alleviate dependency of textual stream on performance of underlying OCR (which is the case with general ...
Muhammad Nabeel Asim +5 more
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Feature Learning for Footnote-Based Document Image Classification
2017Classifying document images is a challenging problem that is confronted by many obstacles; specifically, the pivotal need of hand-designed features and the scarcity of labeled data. In this paper, a new approach for classifying document images, based on the availability of footnotes in them, is presented.
Sherif Abuelwafa +6 more
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Lawsuits Document Images Processing Classification
2022Daniela L. Freire +10 more
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Document image classification: Progress over two decades
Neurocomputing, 2021Taorong Qiu, Qiu Chen
exaly