Usefulness of feature analysis of breast-specific gamma imaging for predicting malignancy
Sign Up to like & getrecommendations! Published in 2018 at "European Radiology"
DOI: 10.1007/s00330-018-5563-3
Abstract: ObjectivesThe purpose of this study was to investigate which feature of the breast-specific gamma imaging (BSGI) uptake in women who were recently diagnosed with breast cancer was associated with malignancy.MethodsData on 231 newly diagnosed breast… read more here.
Keywords: malignancy; feature analysis; mass; breast ... See more keywords
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
Erratum to: Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Mountain Science"
DOI: 10.1007/s11629-017-4497-6
Abstract: The fund name “National Key Technologies R&D Program of China” in the section of “Acknowledgements” is incorrect.The correct fund name is “National Key Research and Development Program of China”. read more here.
Keywords: erratum geometrical; feature analysis; assessment xinmo; analysis disaster ... 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
Sign Up to like & getrecommendations! Published in 2022 at "ACS Omega"
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
Multidimensional Feature Explorer for Unbalanced Spatiotemporal Data
Sign Up to like & getrecommendations! Published in 2019 at "Earth and Space Science"
DOI: 10.1029/2018ea000514
Abstract: Feature analysis of weak nonlinear signals from geographic spatiotemporal data has received increasing attention. Most existing signal processing methods cannot effectively perform comprehensive feature analysis because of the multiple dimensions and unbalance of spatiotemporal data.… read more here.
Keywords: spatiotemporal data; multidimensional feature; feature; feature analysis ... See more keywords
Fault Diagnosis of Wind Turbine Power Converter Considering Wavelet Transform, Feature Analysis, Judgment and BP Neural Network
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2958409
Abstract: The larger capacity of power converters increases with the size of wind turbines over the years, which implies more failures occur in the components of power converter. Meanwhile, the strategies of fault diagnosis of power… read more here.
Keywords: power; feature analysis; analysis judgment; wavelet transform ... 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
Multiple Feature Analysis for Infrared Small Target Detection
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2017.2711047
Abstract: Detection of small target has been an important and challenging task in infrared systems. Most detection algorithms which only use single metric are difficult to separate target from clutter completely. The false alarm may be… read more here.
Keywords: detection; feature analysis; small target; target ... See more keywords