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Next, we give the classification method based on dictionary learning.
In conclusion, we propose for the first time a model of carcinogenesis for metastatic NB based on dictionary learning.
Thus, we used the aCGH data and a statistical inference method based on dictionary learning to propose a Genome Instability Progressive (GIP) model of tumorigenesis for metastatic NB, which has one of the most aggressive known pediatric cancer phenotypes.
Different from most existing artifact removal techniques, we propose a method based on dictionary learning framework.
An effective method for reconstructing a 3D model of human bones from computed tomography (CT) image data based on dictionary learning is proposed.
In this section, we explore a model, based on dictionary learning, that can capture multi-modal structure in the data.
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Bottom row, left to right, reconstruction based on dictionaries learned by BPFA, ITKrMM (L=3) and wKSVD.
This paper proposes a robust pose classification framework based on dictionary-learning and sparse representation.
In this paper, a new algorithm is proposed based on coupled dictionary learning with mapping function for the problem of single-image super-resolution.
The common strategy for NER is either to apply certain rules based on dictionaries and natural language processing techniques (5– 7) or to apply machine learning approaches such as support vector machines (SVMs) and conditional random fields (8– 10).
Therefore, section-heading recognition approaches entirely based on dictionaries or patterns are not always competent.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com