IOFL: Intelligent Optimization-Based Federated Learning for Non-IID Data
X Li, H Zhao, W Deng - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Federated learning (FL) algorithm has been widely studied in recent years due to its ability
for sharing data while protecting privacy. However, FL has risks, such as model inversion …
for sharing data while protecting privacy. However, FL has risks, such as model inversion …
Automatic diagnosis of depression based on facial expression information and deep convolutional neural network
M Li, Y Wang, C Yang, Z Lu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Depression is a complex mental disease, which involves many factors such as psychology,
physiology, and society, and which causes harm to society. Up to now, there are no valuable …
physiology, and society, and which causes harm to society. Up to now, there are no valuable …
Semi-Supervised Adaptive Pseudo-Label Feature Learning for Hyperspectral Image Classification in Internet of Things
Hyperspectral image (HSI) in Internet of Things (IoT) is a typical small sample dataset, which
is difficult and costly to label samples manually. In feature extraction, it is difficult to increase …
is difficult and costly to label samples manually. In feature extraction, it is difficult to increase …
Defect Detection Using Shuffle Net-CA-SSD Lightweight Network for Turbine Blades in IoT
H Zhao, Y Gao, W Deng - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Early detection of blade defects is crucial for turbines in Internet of Things (IoT) as it can
prevent failures, minimize downtime, and enhance system reliability. Deep learning-based …
prevent failures, minimize downtime, and enhance system reliability. Deep learning-based …
Broad Learning System under Label Noise: A Novel Reweighting Framework with Logarithm Kernel and Mixture Autoencoder
J Shen, H Zhao, W Deng - Sensors, 2024 - mdpi.com
The Broad Learning System (BLS) has demonstrated strong performance across a variety of
problems. However, BLS based on the Minimum Mean Square Error (MMSE) criterion is …
problems. However, BLS based on the Minimum Mean Square Error (MMSE) criterion is …
Enhanced Wild Horse Optimizer with Cauchy Mutation and Dynamic Random Search for Hyperspectral Image Band Selection
The high dimensionality of hyperspectral images (HSIs) brings significant redundancy to
data processing. Band selection (BS) is one of the most commonly used dimensionality …
data processing. Band selection (BS) is one of the most commonly used dimensionality …
A hybrid kernel extreme learning machine modeling method based on improved dung beetle algorithm optimization for lithium-ion battery state of health estimation
D Mo, S Wang, M Zhang, Y Fan, Y Wang, J Zeng - Ionics, 2024 - Springer
The state of health (SOH) of lithium-ion batteries is an important indicator for evaluating the
degradation of battery performance, which is crucial in battery management systems. With …
degradation of battery performance, which is crucial in battery management systems. With …
An adaptive differential evolution algorithm with multi-strategy for solving complex optimization problem
Y Li, X Gao, H Ni, Y Song, W Deng - Journal of Intelligent & Fuzzy … - content.iospress.com
In this paper, an adaptive differential evolution algorithm with multi-strategy, namely ESADE
is proposed to solve the premature convergence and high time complexity for complex …
is proposed to solve the premature convergence and high time complexity for complex …