Generative adversarial networks in time series: A systematic literature review

E Brophy, Z Wang, Q She, T Ward - ACM Computing Surveys, 2023 - dl.acm.org
Generative adversarial network (GAN) studies have grown exponentially in the past few
years. Their impact has been seen mainly in the computer vision field with realistic image …

Generative adversarial networks in time series: A survey and taxonomy

E Brophy, Z Wang, Q She, T Ward - arxiv preprint arxiv:2107.11098, 2021 - arxiv.org
Generative adversarial networks (GANs) studies have grown exponentially in the past few
years. Their impact has been seen mainly in the computer vision field with realistic image …

Cross‐scene pavement distress detection by a novel transfer learning framework

Y Li, P Che, C Liu, D Wu, Y Du - Computer‐Aided Civil and …, 2021 - Wiley Online Library
Deep learning has achieved promising results in pavement distress detection. However, the
training model's effectiveness varies according to the data and scenarios acquired by …

The 2023 wearable photoplethysmography roadmap

PH Charlton, J Allen, R Bailón, S Baker… - Physiological …, 2023 - iopscience.iop.org
Photoplethysmography is a key sensing technology which is used in wearable devices such
as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to …

[HTML][HTML] A survey on GANs for computer vision: Recent research, analysis and taxonomy

G Iglesias, E Talavera, A Díaz-Álvarez - Computer Science Review, 2023 - Elsevier
In the last few years, there have been several revolutions in the field of deep learning,
mainly headlined by the large impact of Generative Adversarial Networks (GANs). GANs not …

Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications

J Li, BJ Cairns, J Li, T Zhu - NPJ Digital Medicine, 2023 - nature.com
The recent availability of electronic health records (EHRs) have provided enormous
opportunities to develop artificial intelligence (AI) algorithms. However, patient privacy has …

Generative adversarial network with transformer generator for boosting ECG classification

Y **a, Y Xu, P Chen, J Zhang, Y Zhang - Biomedical Signal Processing and …, 2023 - Elsevier
Arrhythmia is an important group of cardiovascular diseases, which can suddenly attack and
cause sudden death, or continue to affect the heart and cause its failure. Electrocardiogram …

Beyond supervised learning for pervasive healthcare

X Gu, F Deligianni, J Han, X Liu, W Chen… - IEEE Reviews in …, 2023 - ieeexplore.ieee.org
The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …

Anomaly detection in additive manufacturing processes using supervised classification with imbalanced sensor data based on generative adversarial network

J Chung, B Shen, ZJ Kong - Journal of Intelligent Manufacturing, 2024 - Springer
Supervised classification methods have been widely utilized for the quality assurance of the
advanced manufacturing process, such as additive manufacturing (AM) for anomaly …

AI in global health: the view from the front lines

A Ismail, N Kumar - Proceedings of the 2021 CHI Conference on Human …, 2021 - dl.acm.org
There has been growing interest in the application of AI for Social Good, motivated by scarce
and unequal resources globally. We focus on the case of AI in frontline health, a Social …