Human fall detection using slow feature analysis
Sign Up to like & getrecommendations! Published in 2018 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-5638-9
Abstract: Falls are reported to be the leading causes of accidental deaths among elderly people. Automatic detection of falls from video sequences is an assistant technology for low-cost health care systems. In this paper, we present… read more here.
Keywords: feature analysis; slow feature; feature; fall detection ... See more keywords
A Systematic Approach to Dynamic Monitoring of Industrial Processes Based on Second-Order Slow Feature Analysis
Sign Up to like & getrecommendations! Published in 2018 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2018.09.331
Abstract: Abstract Slow feature analysis has proven to be an effective process monitoring and fault diagnosis approach. By isolating temporal behaviors from steady-state variations in process data, slow feature analysis enables a concurrent monitoring of operating… read more here.
Keywords: process; feature analysis; slow feature; order ... See more keywords
Frequency-based slow feature analysis
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.08.067
Abstract: Abstract Slow Feature Analysis (SFA) is an unsupervised learning algorithm which extracts slowly varying features from a temporal vectorial signal. In SFA, feature slowness is measured by the average value of its squared time-derivative. In… read more here.
Keywords: feature analysis; feature; frequency; slow feature ... See more keywords
Concurrent Monitoring Strategy for Static and Dynamic Deviations Based on Selective Ensemble Learning Using Slow Feature Analysis
Sign Up to like & getrecommendations! Published in 2020 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.9b05547
Abstract: Slow feature analysis (SFA) has been extensively adopted for process monitoring. Since the prominent ability of exploring dynamic information of the industrial process, SFA could monitor the proces... read more here.
Keywords: feature analysis; slow feature; concurrent monitoring;
Fault Detection of Non-Gaussian and Nonlinear Processes Based on Independent Slow Feature Analysis
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DOI: 10.1021/acsomega.1c06649
Abstract: Independent component analysis (ICA) is an excellent latent variables (LVs) extraction method that can maximize the non-Gaussianity between LVs to extract statistically independent latent variables and which has been widely used in multivariate statistical process… read more here.
Keywords: slow feature; fault detection; feature analysis; detection ... See more keywords
Anomaly Detection Method for Multimode Complex Industrial Process Based on Multiple Subspaces Slow Feature Analysis
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3107724
Abstract: The multimode operation feature is widely presented in the modern industrial process, which is a typical cyber physical system. In order to achieve the accurate anomaly detection for multimode process, a novel method named multiple… read more here.
Keywords: detection; feature analysis; anomaly detection; slow feature ... See more keywords
Deep Bayesian Slow Feature Extraction With Application to Industrial Inferential Modeling
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2021.3129888
Abstract: Inferential modeling has been of significance for modern manufacturing in estimating the quality-related process variables. As an effective inferential model, probabilistic slow feature analysis (PSFA) has gained attention in regression tasks to interpret dynamic properties… read more here.
Keywords: slow feature; inferential modeling; deep bayesian; feature ... See more keywords
Slow Down to Go Better: A Survey on Slow Feature Analysis.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3201621
Abstract: Temporal data contain a wealth of valuable information, playing an essential role in various machine-learning tasks. Slow feature analysis (SFA), one of the most classic temporal feature extraction models, has been deeply explored in two… read more here.
Keywords: slow better; slow feature; feature; feature analysis ... See more keywords