Privacy inference attack against users in online social networks: a literature review

Y Piao, K Ye, X Cui - IEEE Access, 2021 - ieeexplore.ieee.org
With the rapid development of social networks, users pay more and more attention to the
protection of personal information. However, the transmission of users' personal information …

An intelligent fault diagnosis method for rotating machinery based on data fusion and deep residual neural network

B Peng, H Xia, X Lv, M Annor-Nyarko, S Zhu, Y Liu… - Applied …, 2022 - Springer
Rotating machinery is a very important mechanical device widely used in critical industrial
applications. Efficient fault detection and diagnosis are key challenges in the maintenance …

A hybrid approach with gan and dp for privacy preservation of iiot data

YS Hindistan, EF Yetkin - IEEE Access, 2023 - ieeexplore.ieee.org
There are emerging trends to use the Industrial Internet of Things (IIoT) in manufacturing and
related industries. Machine Learning (ML) techniques are widely used to interpret the …

Remote sensing image colorization using symmetrical multi-scale DCGAN in YUV color space

M Wu, X Jin, Q Jiang, S Lee, W Liang, G Lin, S Yao - The Visual Computer, 2021 - Springer
Image colorization technique is used to colorize the gray-level image or single-channel
image, which is a very significant and challenging task in image processing, especially the …

Predicting bacterial transport through saturated porous media using an automated machine learning model

F Chen, B Zhou, L Yang, X Chen… - Frontiers in Microbiology, 2023 - frontiersin.org
Escherichia coli, as an indicator of fecal contamination, can move from manure-amended
soil to groundwater under rainfall or irrigation events. Predicting its vertical transport in the …

A review of hybrid cyber threats modelling and detection using artificial intelligence in IIoT

Y Liu, S Li, X Wang, L Xu - Computer Modeling in …, 2024 - digitalcommons.odu.edu
Abstract The Industrial Internet of Things (IIoT) has brought numerous benefits, such as
improved efficiency, smart analytics, and increased automation. However, it also exposes …

E-Tanh: a novel activation function for image processing neural network models

T Kalaiselvi, ST Padmapriya, K Somasundaram… - Neural Computing and …, 2022 - Springer
Artificial neural network (ANN) is one of the technologies used for emerging real-world
problems. Activation functions (AF) are used in deep learning architectures to make …

Multi-generator GAN learning disconnected manifolds with mutual information

W Li, Z Liang, J Neuman, J Chen, X Cui - Knowledge-Based Systems, 2021 - Elsevier
Original data usually lies on a set of disconnected manifolds rather than a smooth connected
manifold. This causes the problem of mode collapse in the training of vanilla Generative …

Securely computing the manhattan distance under the malicious model and its applications

X Liu, X Liu, R Zhang, D Luo, G Xu, X Chen - Applied Sciences, 2022 - mdpi.com
Manhattan distance is mainly used to calculate the total absolute wheelbase of two points in
the standard coordinate system. The secure computation of Manhattan distance is a new …

Sketch-then-edit generative adversarial network

W Li, L Xu, Z Liang, S Wang, J Cao, C Ma… - Knowledge-Based Systems, 2020 - Elsevier
Abstract Generative Adversarial Network (GAN) has been widely used to generate
impressively plausible data. However, it is a non-trivial task to train the original GAN model …