Results 241 to 250 of about 598,648 (280)

AI-enhanced clustering of mine tailings using Geostatistical data augmentation and Gaussian mixture models. [PDF]

Sci Rep
Madani N, Sabanov S.
europepmc   +1 more source

Synthetic Orthopantomography Image Generation Using Generative Adversarial Networks for Data Augmentation. [PDF]

Int Dent J
Waqas M, Hasan S, Ghori AF, Alfaraj A, Faheemuddin M, Khurshid Z.   +5 more
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AI Grading of Lateral Canthal Lines: Novel Models for Unseen Synthetic Image Generation and Data Augmentation. [PDF]

Clin Cosmet Investig Dermatol
Yang TT, Ma CW, Lee CH, Qiu SX, Lan CE.
europepmc   +1 more source

Going beyond SMILES enumeration for data augmentation in generative drug discovery.

Digit Discov
Brinkmann H, Argante A, Ter Steege H, Grisoni F.   +3 more
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3D Segmentation of Multi-Contrast Cardiac Magnetic Resonances With Topological Correction and Synthetic Data Augmentation

Rosales RM, Doblaré M, Pueyo E.
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

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
openaire   +1 more source

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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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
openaire   +2 more sources

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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