Results 81 to 90 of about 1,572,835 (188)

FaultFormer: Pretraining Transformers for Adaptable Bearing Fault Classification

IEEE Access
The growth of global consumption has motivated important applications of deep learning to smart manufacturing and machine health monitoring. In particular, analyzing vibration data offers great potential to extract meaningful insights into predictive ...
Anthony Y. Zhou, Amir Barati Farimani
doaj   +1 more source

Identification of High Energy Gamma Particles From the Cherenkov Gamma Telescope Data Using a Deep Learning Approach

IEEE Access
Atmospheric Cherenkov telescopes have enabled recent breakthroughs in gamma-ray astronomy, enabling the study of high-energy gamma particles in over 90 galactic and extragalactic regions.
K. Karthick, S. Akila Agnes, S. Sendil Kumar, Sultan Alfarhood, Mejdl Safran   +4 more
doaj   +1 more source

Multi‐view synergistic enhanced fault recording data for transmission line fault classification

IET Communications
Fault recorded data has been proven to be effective for fault diagnosis of overhead transmission lines. Utilizing deep learning to mine potential fault patterns in fault recording data is an inevitable trend.
Minghui Jia, Xiaohu Huang, Fengjun Han, Dequan Yan, Wei Wang, Guochao Zhu, Lin Zhang, Chao Pan, Haifeng Ma, Jidong Wei   +9 more
doaj   +1 more source

Radar‐based human activity recognition using denoising techniques to enhance classification accuracy

IET Radar, Sonar & Navigation
Radar‐based human activity recognition is considered as a competitive solution for the elderly care health monitoring problem, compared to alternative techniques such as cameras and wearable devices. However, raw radar signals are often contaminated with
Ran Yu, Yaxin Du, Jipeng Li, Antonio Napolitano, Julien Le Kernec   +4 more
doaj   +1 more source

Temporal signals classification

, 2017
Nowadays, there are a lot of applications related to machine vision and hearing which tried to reproduce human capabilities on machines. These problems are mainly amenable to a temporal signals classification problem, due our interest to this subject.
openaire   +1 more source

Interactive learning of natural sign language with radar

IET Radar, Sonar & Navigation
Over the past decade, there have been great advancements in radio frequency sensor technology for human–computer interaction applications, such as gesture recognition, and human activity recognition more broadly.
Emre Kurtoğlu, Kenneth DeHaan, Caroline Kobek Pezzarossi, Darrin J. Griffin, Chris Crawford, Sevgi Z. Gurbuz   +5 more
doaj   +1 more source

Efficient Multiple Channels EEG Signal Classification Based on Hierarchical Extreme Learning Machine. [PDF]

Sensors (Basel), 2023
Lyu S, Cheung RCC.
europepmc   +1 more source

Differential quadruple pattern: A new EEG signal classification framework. [PDF]

IBRO Neurosci Rep
Ozgor B, Goktas OF, Baygin M, Dogan S, Tuncer T.   +4 more
europepmc   +1 more source

ECG signal classification in wearable devices based on compressed domain. [PDF]

PLoS One, 2023
Hua J, Chu B, Zou J, Jia J.
europepmc   +1 more source

Multi-target passive positioning with signal classification and MIMO radar. [PDF]

Sci Rep
Wang H, Liu X, Lei Z.
europepmc   +1 more source