Results 51 to 60 of about 24,031,398 (300)
Current Directions in Biomedical Engineering, 2021 Data augmentation is a common method to make deep learning assessible on limited data sets. However, classical image augmentation methods result in highly unrealistic images on ultrasound data.
Wulff Daniel +3 more
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Application of a predictive distribution formula to Bayesian computation for incomplete data models [PDF]
, 2005 We consider exact and approximate Bayesian computation in the presence of latent variables or missing data. Specifically we explore the application of a posterior predictive distribution formula derived in Sweeting And Kharroubi (2003), which is a ...
Sweeting, T +3 more
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Data augmentation strategies to improve reaction yield predictions and estimate uncertainty [PDF]
, 2020 Chemical reactions describe how precursor molecules react together and transform into products. The reaction yield describes the percentage of the precursors successfully transformed into products relative to the theoretical maximum.
Alain C., Vaucher +3 more
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Brainwave Classification Using Covariance-Based Data Augmentation
IEEE Access, 2020 A brain-machine interface (BMI) is a technology that controls machines via brainwaves. In BMI, the performance of brainwave analysis is very important for achieving machine control that reflects the user's intention.
Wonseok Yang, Woochul Nam
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Informatics in Medicine Unlocked, 2021 Successful training of convolutional neural networks (CNNs) requires a substantial amount of data. With small datasets, networks generalize poorly. Data Augmentation techniques improve the generalizability of neural networks by using existing training ...
Saman Motamed +2 more
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Style Augmentation: Data Augmentation via Style Randomization [PDF]
, 2019 We introduce style augmentation, a new form of data augmentation based on random style transfer, for improving the robustness of Convolutional Neural Networks (CNN) over both classification and regression based tasks.
Atapour-Abarghouei, Amir +4 more
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To Augment or Not to Augment? Data Augmentation in User Identification Based on Motion Sensors [PDF]
, 2020 Nowadays, commonly-used authentication systems for mobile device users, e.g. password checking, face recognition or fingerprint scanning, are susceptible to various kinds of attacks. In order to prevent some of the possible attacks, these explicit authentication systems can be enhanced by considering a two-factor authentication scheme, in which the ...
Cezara Benegui, Radu Tudor Ionescu
openaire +3 more sources
Transfer Incremental Learning Using Data Augmentation
Applied Sciences, 2018 Deep learning-based methods have reached state of the art performances, relying on a large quantity of available data and computational power. Such methods still remain highly inappropriate when facing a major open machine learning problem, which ...
Ghouthi Boukli Hacene +4 more
doaj +1 more source
Dynamic causal model application on hierarchical human motor control estimation in visuomotor tasks
Frontiers in NeurologyIntroductionIn brain function research, each brain region has been investigated independently, and how different parts of the brain work together has been examined using the correlations among them.
Ningjia Yang +6 more
doaj +1 more source
Image augmentation techniques for convolutional neural network [PDF]
, 2022 openUna delle più grandi sfide per le Reti Neurali Convoluzionali, soprattutto ora che vengono utilizzate ampiamente in svariati contesti, è la mancanza di training set adeguati per sessioni di training robuste e meno prone ad overfitting.
BRAVIN, RICCARDO
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