Results 271 to 280 of about 252,636 (309)

Data Augmentation and Synthetic Data Generation in Rare Disease Research: A Scoping Review. [PDF]

Med Sci (Basel)
Finetti R, Roncaglia B, Visibelli A, Spiga O, Santucci A.   +4 more
europepmc   +1 more source

Parameter-expanded data augmentation for analyzing multinomial probit models. [PDF]

Commun Stat Theory Methods
Zhang X.
europepmc   +1 more source

Correction: Enhancing buckwheat maturity classification with generative adversarial networks for spectroscopy data augmentation. [PDF]

Front Plant Sci
Wang H, Che X, Nan J, Miao Y, Wang Y, Zhang W, Li F, Han J.   +7 more
europepmc   +1 more source

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Visually Augmenting Documents With Data

Computing in Science & Engineering, 2018
“ A picture is worth a thousand words ” is a famous English saying. It is true in many cases, because a complex idea or data can be simply conveyed through the use of a single static image or diagram. Therefore, inclusion of graphics and visualizations in scientific texts has been an important aspect ever since researchers started publishing articles ...
Latif, Shahid, Beck, Fabian
openaire   +2 more sources

Active Image Data Augmentation

2019
Deep neural networks models have achieved state-of-the-art results in a great number of different tasks in different domains (e.g., natural language processing and computer vision). However, the notions of robustness, causality, and fairness are not measured in traditional evaluated settings. In this work, we proposed an active data augmentation method
Flávio Arthur Oliveira Santos, Cleber Zanchettin, Leonardo Nogueira Matos, Paulo Novais   +3 more
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Augmenting Data Warehouses with Big Data

Information Systems Management, 2015
In the past decade, corporations are increasingly engaging in efforts whose aim is the analysis and wide-ranging use of big data. The majority of academic big data articles have been focused on methods, approaches, opportunities, and organizational impact of big data analytics.
Nenad Jukic, Abhishek Sharma 0003, Svetlozar Nestorov, Boris Jukic   +3 more
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Rotational data augmentation for electroencephalographic data

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017
For deep learning on image data, a common approach is to augment the training data by artificial new images, using techniques like moving windows, scaling, affine distortions, and elastic deformations. In contrast to image data, electroencephalographic (EEG) data suffers even more from the lack of sufficient training data.We suggest and evaluate ...
Mario Michael Krell, Su Kyoung Kim
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Data Augmentation for Neuroaesthetics Analysis

Neuroaesthetics investigates the neural activities during aesthetic experiences, using EEG recordings or fMRI images to decode the perception of visual art. However, studies in this domain are hindered by the limited and imbalanced nature of datasets, which is due to the subjective and resource-intensive nature of data collection.
Maurizio Palmieri, Marco Avvenuti, Francesco Marcelloni, Alessio Vecchio   +3 more
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Data Augmentation from Sketch

2019
State of the art machine learning methods need huge amounts of data with unambiguous annotations for their training. In the context of medical imaging this is, in general, a very difficult task due to limited access to clinical data, the time required for manual annotations and variability across experts.
Debora Gil, Antonio Esteban-Lansaque, Sebastian Stefaniga, Mihail Gaianu, Carles Sánchez   +4 more
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On the use of Correlation to Augment Data

Journal of the American Statistical Association, 1962
Abstract This paper provides an evaluation of the effects of a particular regression-estimation technique used to augment measurements when concurrent and additional measurements are available for two other variates. The investigation demonstrates that this use of regression does not always produce better estimates of population parameters, and indeed,
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