Results 61 to 70 of about 1,309,182 (144)

Multiscale Cumulative Residual Dispersion Entropy with Applications to Cardiovascular Signals

, 2023
Heart rate variability (HRV) is used as an index reflecting the adaptability of the autonomic nervous system to external stimuli and can be used to detect various heart diseases.
Young-Seok Choi, Youngjun Kim
core   +1 more source

Denoising method for partial discharge signals of high-voltage mining cables

Gong-kuang zidonghua
Currently, partial discharge (PD) signals of high-voltage mining cables are easily buried in noise and difficult to extract. Variational Mode Decomposition (VMD) is an effective method for PD denoising, but the number of decomposition layers and penalty ...
ZHANG Xiaoniu, SI Shijun, LI Junhong, WANG Anle   +3 more
doaj   +1 more source

FEWT: Frequency‐Enhanced Wavelet‐Based Transformer for Multimodal Wheeled Bimanual Manipulation

SmartBot, EarlyView.
An embodied mobile bimanual robot learns dexterous manipulation skills through imitation learning with multimodal perception. The integration of vision, proprioception, and tactile sensing establishes a comprehensive perception–action loop, enabling the robot to continuously understand, interact with, and adapt to complex physical environments.
Jiaxin Huang, Hanyu Liu, Yunsheng Ma, Jian Shen, Yilin Zheng, Jiayi Wen, Zhigong Song   +6 more
wiley   +1 more source

Gearbox Fault Diagnosis Based on Refined Time-Shift Multiscale Reverse Dispersion Entropy and Optimised Support Vector Machine

, 2023
The fault diagnosis of a gearbox is crucial to ensure its safe operation. Entropy has become a common tool for measuring the complexity of time series. However, entropy bias may occur when the data are not long enough or the scale becomes larger.
Xiang Wang, Han Jiang
core   +1 more source

A Wildlife Multi‐Modal Recognition Method Based on Infrared Camera Images Using MWAC

Integrative Zoology, EarlyView.
A multimodal wild wildlife classification model MWAC consists of two parts:(1) Wavelet KAN module (WDS‐KAN) for image feature extraction, and (2) Label Correlated Text Extraction module (LC‐BERT) for text feature extraction. ABSTRACT Nowadays, infrared camera technology has become an important tool for large‐scale monitoring and assessment of wildlife ...
Siming Deng, Guoxiong Zhou, Genhua Liu, Zhishu Xiao, Xiaoqun Huang, Yang Hu, Ling Gui   +6 more
wiley   +1 more source

Effects of repetitive SSVEPs on EEG complexity using multiscale inherent fuzzy entropy

, 2020
Multiscale inherent fuzzy entropy is an objective measurement of electroencephalography (EEG) complexity, reflecting the habituation of brain systems.
Ding, W (15681284), Hussain, FK (15692738), Cao, Z (15687902), Lin, C-T (15687899), Wang, Y-K (15688904), Al-Jumaily, A (15692741)   +5 more
core  

Controllable Intrinsic Surface Pattern Generation Using Slime Mold Simulations

Computer Graphics Forum, EarlyView.
Abstract Surface‐based pattern simulations have proven valuable for texture design and scientific visualization, but existing methods face several limitations. Most simulations either target a narrow range of pattern types (e.g. spots, branching) or support a broad range of patterns at the cost of time‐consuming parameter tuning.
Jeffrey Layton, Faramarz Samavati, Adam Runions   +2 more
wiley   +1 more source

KPI‐NeRF: Hyperspectral Neural Radiance Fields from a Single Kaleidoscopic Plenoptic Image

Computer Graphics Forum, EarlyView.
KPI‐NeRF reconstructs hyperspectral light field images from a single kaleidoscopic plenoptic image. By leveraging neural radiance fields, it enables high‐quality spectral and angular de‐multiplexing for dynamic scene capture. Abstract Plenoptic imaging has excessive sampling requirements associated with the high dimensionality of the desired data.
Erqi Huang, John Restrepo, Xun Cao, Ivo Ihrke   +3 more
wiley   +1 more source

Leveraging modified ex situ tomography data for segmentation of in situ synchrotron X‐ray computed tomography

Journal of Microscopy, EarlyView.
Abstract In situ synchrotron X‐ray computed tomography enables dynamic material studies. However, automated segmentation remains challenging due to complex imaging artefacts – like ring and cupping effects – and limited training data. We present a methodology for deep learning‐based segmentation by transforming high‐quality ex situ laboratory data to ...
Tristan Manchester, Adam Anders, Julio Spadotto, Hannah Eccleston, William Beavan, Hugues Arcis, Brian J. Connolly   +6 more
wiley   +1 more source

Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

, 2017
Electroencephalography (EEG) is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG) not only has a close correlation with the human imagination and movement intention but ...
Ming-ai Li, Jin-fu Yang, Hai-na Liu, Wei Zhu   +3 more
core   +1 more source