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Document Image Classification with Vision Transformers
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 2022© 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.Document image classification has received huge interest in business automation processes. Therefore, document image classification plays an important role in the document image processing (DIP) systems.
Semih Sevim +2 more
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Turkish Document Image Classification
Document image classification has gained extensive attentiondue to the rising number and types of scanned documents. Multimodalarchitectures, processing image and text simultaneously, leveragethe strengths of each modality. This study explores an efficient neuralarchitecture for classifying scanned documents in a private company.The effectiveness of ...
Meryem Tuğba Nar +5 more
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Hidden tree markov models for document image classification
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003Classification is an important problem in image document processing and is often a preliminary step toward recognition, understanding, and information extraction. In this paper, the problem is formulated in the framework of concept learning and each category corresponds to the set of image documents with similar physical structure.
P Frasconi
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Document image classification using SEMCON
2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA), 2015 In this paper, we are proposing a new semantic and contextual based document image classification framework. The framework is composed of two main modules. The first one is the text analysis module (TAM) which processes document images and extracts words from the image, and second one is the SEMCON, which is a semantic and contextual objective metric ...
Zenun Kastrati, Ali Shariq Imran
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Multimodal Document Image Classification
2019 International Conference on Document Analysis and Recognition (ICDAR), 2019State-of-the-art methods for document image classification rely on visual features extracted by deep convolutional neural networks (CNNs). These methods do not utilize rich semantic information present in the text of the document, which can be extracted using Optical Character Recognition (OCR).
Rajiv Jain, Curtis Wigington
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Document image layout comparison and classification
Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318), 1999The paper describes features and methods for document image comparison and classification at the spatial layout level. The methods are useful for visual similarity based document retrieval as well as fast algorithms for initial document type classification without OCR.
Jianying Hu +2 more
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Multimodal Classification of Document Embedded Images
2018Images embedded in documents carry extremely rich information that is vital in its content extraction and knowledge construction. Interpreting the information in diagrams, scanned tables and other types of images, enriches the underlying concepts, but requires a classifier that can recognize the huge variability of potential embedded image types and ...
Matheus P. Viana +3 more
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Two Level Document Image Classification
2021 6th International Conference on Computer Science and Engineering (UBMK), 2021Classifying documents is an important process for organizations that are responsible for keeping a large number of documents in a digital archive. In this paper, a two-level method was used to classify approximately 253 class of documents. In the first stage, the documents were visually classified.
Adnan Oncevarlik +3 more
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Structural similarity for document image classification and retrieval
Pattern Recognition Letters, 2014Abstract This paper presents a novel approach to defining document image structural similarity for the applications of classification and retrieval. We first build a codebook of SURF descriptors extracted from a set of representative training images.
Jayant Kumar +2 more
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