A comprehensive review of extreme learning machine on medical imaging
The feedforward neural network based on randomization has been of great interest in the
scientific community, particularly extreme learning machines, due to its simplicity, training …
scientific community, particularly extreme learning machines, due to its simplicity, training …
Model architecture level privacy leakage in neural networks
Privacy leakage is one of the most critical issues in machine learning and has attracted
growing interest for tasks such as demonstrating potential threats in model attacks and …
growing interest for tasks such as demonstrating potential threats in model attacks and …
An instance-based deep transfer learning method for quality identification of Long**g tea from multiple geographical origins
C Zhang, J Wang, T Yan, X Lu, G Lu, X Tang… - Complex & Intelligent …, 2023 - Springer
For practitioners, it is very crucial to realize accurate and automatic vision-based quality
identification of Long**g tea. Due to the high similarity between classes, the classification …
identification of Long**g tea. Due to the high similarity between classes, the classification …
Robust online active learning with cluster-based local drift detection for unbalanced imperfect data
With the rapid development of data-driven technologies, a massive amount of actual data
emerges from industrial systems, forming data stream. Their data distribution may change …
emerges from industrial systems, forming data stream. Their data distribution may change …
Amplitude-based multiscale reverse dispersion entropy: a novel approach to bearing fault diagnosis
The multiscale fluctuation dispersion entropy algorithm (MFDE) is widely used to extract the
characteristics from a variety of complex nonlinear signals, including bearing signals, due to …
characteristics from a variety of complex nonlinear signals, including bearing signals, due to …
Residual deep fuzzy system with randomized fuzzy modules for accurate time series forecasting
Y Liu, W Peng, H Wang, C Li, X Lu - Neural Computing and Applications, 2024 - Springer
The data-driven modular deep fuzzy model has demonstrated excellent forecasting
performance due to its clear architecture and powerful fuzzy inference ability. However, the …
performance due to its clear architecture and powerful fuzzy inference ability. However, the …
[HTML][HTML] Fault prognosis of wind turbines using multimodal machine learning
Wind turbines (WT) convert wind's kinetic energy into electrical energy, providing
sustainable electricity. However, all machines eventually experience performance decline …
sustainable electricity. However, all machines eventually experience performance decline …