Results 11 to 20 of about 11,612 (265)
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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Binarity and Stellar Evolution [PDF]
Proceedings of the International Astronomical Union, 2011 AbstractModels of stellar evolution constitute an extremely powerful, and for the most part apparently very successful, tool for understanding the progression of a star through its lifetime as a fairly compact entity of incandescent gas. That success has led to stellar evolution theory becoming a crutch when an observer is faced with objects whose ...
Griffin, R. E. M., Rucinski, Slavek
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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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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.
Guillaume Lazzara, Thierry Géraud
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Binarized Encoder-Decoder Network and Binarized Deconvolution Engine for Semantic Segmentation [PDF]
IEEE Access, 2021 Recently, semantic segmentation based on deep neural network (DNN) has attracted attention as it exhibits high accuracy, and many studies have been conducted on this. However, DNN-based segmentation studies focused mainly on improving accuracy, thus greatly increasing the computational demand and memory footprint of the segmentation network.
Hyunwoo Kim +4 more
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η Carinae: Binarity Confirmed [PDF]
The Astrophysical Journal, 2000 13 pages, accepted by ApJ Letters (January 2000)
Damineli, Augusto +5 more
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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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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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