A systematic guide for predicting remaining useful life with machine learning

T Berghout, M Benbouzid - Electronics, 2022 - mdpi.com
Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of
damage propagation and aging of operating systems during working conditions. More …

[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 …

Imbalanced data classification: A KNN and generative adversarial networks-based hybrid approach for intrusion detection

H Ding, L Chen, L Dong, Z Fu, X Cui - Future Generation Computer Systems, 2022 - Elsevier
With the continuous emergence of various network attacks, it is becoming more and more
important to ensure the security of the network. Intrusion detection, as one of the important …

Momentum contrastive learning for few-shot COVID-19 diagnosis from chest CT images

X Chen, L Yao, T Zhou, J Dong, Y Zhang - Pattern recognition, 2021 - Elsevier
The current pandemic, caused by the outbreak of a novel coronavirus (COVID-19) in
December 2019, has led to a global emergency that has significantly impacted economies …

A multi-stage underwater image aesthetic enhancement algorithm based on a generative adversarial network

K Hu, C Weng, C Shen, T Wang, L Weng… - Engineering Applications of …, 2023 - Elsevier
Existing underwater image enhancement algorithms rely on paired datasets, which enhance
underwater images by learning the map** relationship between low-quality and high …

Integrated generative model for industrial anomaly detection via bidirectional LSTM and attention mechanism

F Kong, J Li, B Jiang, H Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
For emerging industrial Internet of Things (IIoT), intelligent anomaly detection is a key step to
build smart industry. Especially, explosive time-series data pose enormous challenges to the …

A review on blockchain smart contracts in the agri-food industry: Current state, application challenges and future trends

X Peng, Z Zhao, X Wang, H Li, J Xu, X Zhang - Computers and Electronics …, 2023 - Elsevier
With the continuous development of the new crown epidemic and the outbreak of the
Russian-Ukrainian war, the world is facing a serious food crisis, especially the agri-food …

EID-GAN: Generative adversarial nets for extremely imbalanced data augmentation

W Li, J Chen, J Cao, C Ma, J Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Imbalanced data cause deep neural networks to output biased results, and it becomes more
serious when facing extremely imbalanced data regarding the outliers with tiny size (the …

Ifl-gan: Improved federated learning generative adversarial network with maximum mean discrepancy model aggregation

W Li, J Chen, Z Wang, Z Shen, C Ma… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The generative adversarial network (GAN) is usually built from the centralized, independent
identically distributed (iid) training data to generate realistic-like instances. In real-world …

Underwater light field retention: Neural rendering for underwater imaging

T Ye, S Chen, Y Liu, Y Ye… - Proceedings of the …, 2022 - openaccess.thecvf.com
Abstract Underwater Image Rendering aims to generate a true-to-life underwater image from
a given clean one, which could be applied to various practical applications such as …