Results 41 to 50 of about 207,018 (117)

Data Augmentation Techniques for fMRI Data: A Technical Survey

IEEE Access
The application of machine learning to fMRI data classification, prediction, and analysis tasks has experienced rapid growth in recent years. However, its implementation has been limited by the relatively small size of labeled fMRI datasets.
Valentina Sanchez, Cicek Guven, Gonzalo Napoles, Marie Safar Postma   +3 more
doaj   +1 more source

CycleGAN Variants for Industrial Defect Data Augmentation [PDF]

ITM Web of Conferences
Industrial visual inspection is constrained by scarce labeled defect samples and complex surface patterns in bearings, steel, and ICs, significantly hindering deep learning detection models.
Xu Xiaoyu
doaj   +1 more source

TATS: toolbox for time series data augmentation [PDF]

PeerJ Computer Science
Augmenting time series data plays a crucial role in enhancing the generalization of classification models, especially in scenarios where labeled datasets are limited.
Dawid Warchoł, Mariusz Oszust
doaj   +2 more sources

Comparative Analysis of Conventional and Focused Data Augmentation Methods in Rib Fracture Detection in CT Images

Diagnostics
Background/Objectives: Rib fracture detection holds critical importance in the field of medical image processing. Methods: In this study, two different data augmentation methods, traditional data augmentation (Albumentations) and focused data ...
Mehmet Çağrı Göktekin, Evrim Gül, Feyza Aksu, Yeliz Gül, Metehan Özen, Yusuf Salik, Merve Kesim Önal, Engin Avci   +7 more
doaj   +1 more source

A systematic review of deep learning data augmentation in medical imaging: Recent advances and future research directions

Healthcare Analytics
Data augmentation involves artificially expanding a dataset by applying various transformations to the existing data. Recent developments in deep learning have advanced data augmentation, enabling more complex transformations.
Tauhidul Islam, Md. Sadman Hafiz, Jamin Rahman Jim, Md. Mohsin Kabir, M.F. Mridha   +4 more
doaj   +1 more source

Fast data augmentation for battery degradation prediction

Energy and AI
Degradation prediction for lithium-ion batteries using data-driven methods requires high-quality aging data. However, generating such data, whether in the laboratory or the field, is time- and resource-intensive.
Weihan Li, Harshvardhan Samsukha, Bruis van Vlijmen, Lisen Yan, Samuel Greenbank, Simona Onori, Venkat Viswanathan   +6 more
doaj   +1 more source

Time-series representation learning via Time-Frequency Fusion Contrasting

Frontiers in Artificial Intelligence
Time series is a typical data type in numerous domains; however, labeling large amounts of time series data can be costly and time-consuming. Learning effective representation from unlabeled time series data is a challenging task.
Wenbo Zhao, Ling Fan
doaj   +1 more source

Targeted Data Augmentation for Improving Model Robustness

International Journal of Applied Mathematics and Computer Science
This paper proposes a new and effective bias mitigation method called targeted data augmentation (TDA). Since removing biases is often tedious and challenging and may not always lead to effective bias mitigation, we propose an alternative approach ...
Mikołajczyk-Bareła Agnieszka, Ferlin Maria, Grochowski Michał   +2 more
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Air Target ISAR Recognition Based on Data Augmentation and Transfer Learning. [PDF]

Sensors (Basel)
Wang M, Huang Z, Cai J, Wu T, Lin Y.
europepmc   +1 more source

Illumination-targeting Data Augmentation for Monochrome Images [PDF]

Annals of computer science and information systems
Andrzej Śluzek, Piotr Stachura
doaj   +1 more source