Results 11 to 20 of about 32,202 (267)
Engineering Proceedings, 2023 Contour detection with good accuracy is challenging in various computer-aided measurement applications. This paper evaluates the performance and comparison of thresholding and edge detection techniques for contour measurement along with character ...
Nehal Abdul Rehman, Farah Haroon
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IEEE Access, 2021 Machine learning techniques heavily rely on available training data in a data set. Certain features in the data can interfere with the learning process, so it is required to remove irrelevant and redundant features to build a robust training model.
Thaer Thaher +5 more
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Efficient multiscale Sauvola’s binarization [PDF]
International Journal on Document Analysis and Recognition (IJDAR), 2013 This work focuses on the most commonly used binarization method: Sauvola's. It performs relatively well on classical documents, however, three main defects remain: the window parameter of Sauvola's formula does not fit automatically to the contents, it is not robust to low contrasts, and it is not invariant with respect to contrast inversion.
Lazzara, Guillaume, Géraud, Thierry
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Mathematics, 2020 Metaheuristics are smart problem solvers devoted to tackling particularly large optimization problems. During the last 20 years, they have largely been used to solve different problems from the academic as well as from the real-world.
Sergio Valdivia +6 more
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Binarization, synchronous binarization, and target-side binarization [PDF]
Proceedings of the NAACL-HLT 2007/AMTA Workshop on Syntax and Structure in Statistical Translation - SSST '07, 2007 Binarization is essential for achieving polynomial time complexities in parsing and syntax-based machine translation. This paper presents a new binarization scheme, target-side binarization, and compares it with source-side and synchronous binarizations on both string-based and tree-based systems using synchronous grammars.
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Binarized Support Vector Machines [PDF]
INFORMS Journal on Computing, 2010 The widely used support vector machine (SVM) method has shown to yield very good results in supervised classification problems. Other methods such as classification trees have become more popular among practitioners than SVM thanks to their interpretability, which is an important issue in data mining.In this work, we propose an SVM-based method that ...
Romero Morales, Dolores +2 more
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Компьютерная оптика, 2023 Text recognition has benefited considerably from deep learning research, as well as the preprocessing methods included in its workflow. Identity documents are critical in the field of document analysis and should be thoroughly researched in relation to ...
R. Sánchez-Rivero +5 more
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Using Paper Texture for Choosing a Suitable Algorithm for Scanned Document Image Binarization
Journal of Imaging, 2022 The intrinsic features of documents, such as paper color, texture, aging, translucency, the kind of printing, typing or handwriting, etc., are important with regard to how to process and enhance their image. Image binarization is the process of producing
Rafael Dueire Lins +3 more
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DeepOtsu: Document Enhancement and Binarization using Iterative Deep Learning [PDF]
, 2019 This paper presents a novel iterative deep learning framework and apply it for document enhancement and binarization. Unlike the traditional methods which predict the binary label of each pixel on the input image, we train the neural network to learn the
He, Sheng, Schomaker, Lambert
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Choroidal Vascularity Index and Choroidal Thickness Changes Following Renal Transplantation
Türk Oftalmoloji Dergisi, 2023 Objectives:This study aimed to evaluate changes in subfoveal choroidal thickness (SFCT), choroidal vascularity index (CVI), estimated glomerular filtration rate (GFR), mean arterial pressure (MAP), and intraocular pressure (IOP) after renal ...
Mustafa Aksoy +5 more
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