Results 31 to 40 of about 598,648 (280)
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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Data augmentation for galaxy density map reconstruction [PDF]
, 2011 The matter density is an important knowledge for today cosmology as many phenomena are linked to matter fluctuations. However, this density is not directly available, but estimated through lensing maps or galaxy surveys.
Dupé, François-Xavier +2 more
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Unsupervised learning using topological data augmentation
Physical Review Research, 2020 Unsupervised machine learning is a cornerstone of artificial intelligence as it provides algorithms capable of learning tasks, such as classification of data, without explicit human assistance.
Oleksandr Balabanov, Mats Granath
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Medical Augmentation (Med-Aug) for Optimal Data Augmentation in Medical Deep Learning Networks
Sensors, 2021 Deep learning (DL) algorithms have become an increasingly popular choice for image classification and segmentation tasks; however, their range of applications can be limited.
Justin Lo +3 more
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Data Augmentation for Low-Resource Neural Machine Translation [PDF]
, 2017 The quality of a Neural Machine Translation system depends substantially on the availability of sizable parallel corpora. For low-resource language pairs this is not the case, resulting in poor translation quality. Inspired by work in computer vision, we
Bisazza, Arianna +2 more
core +2 more sources
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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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
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Data Augmentation For Label Enhancement
CoRR, 2023 Label distribution (LD) uses the description degree to describe instances, which provides more fine-grained supervision information when learning with label ambiguity. Nevertheless, LD is unavailable in many real-world applications. To obtain LD, label enhancement (LE) has emerged to recover LD from logical label.
Zhiqiang Kou +4 more
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Data Augmentation for Mathematical Objects [PDF]
CoRR, 2023 10 pages.
Tereso del Río, Matthew England 0001
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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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