Results 51 to 60 of about 493,672 (330)
A hybrid nonlinear-discriminant analysis feature projection technique [PDF]
, 2008 Feature set dimensionality reduction via Discriminant Analysis (DA) is one of the most sought after approaches in many applications. In this paper, a novel nonlinear DA technique is presented based on a hybrid of Artificial Neural Networks (ANN) and the ...
A.R. Webb +9 more
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IEEE Access, 2022 The human hand needs a large number of sensors to measure kinematics owing to its large number of degrees of freedom. Existing devices like data gloves and optical trackers are associated with calibration, line of sight, and accuracy problems.
Prajwal Shenoy +2 more
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eLife, 2021 Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only
Eric Kenji Lee +6 more
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Probabilistic Nonlinear Dimensionality Reduction
, 2022 High-dimensional datasets are present across scientific disciplines. In the analysis of such datasets, dimensionality reduction methods which provide clear interpretations of their model parameters are required. Principal components analysis (PCA) has long been a preferred method for linear dimensionality reduction, but is not recommended for data ...
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Semisupervised Kernel Marginal Fisher Analysis for Face Recognition
The Scientific World Journal, 2013 Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA ...
Ziqiang Wang +3 more
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NON-LINEAR AUTOENCODER BASED ALGORITHM FOR DIMENSIONALITY REDUCTION OF AIRBORNE HYPERSPECTRAL DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Hyperspectral remote sensing is an advanced remote sensing technology that enhances the ability of accurate classification due to presence of narrow contiguous bands.
S. Priya, R. Ghosh, B. K. Bhattacharya
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Optimized kernel minimum noise fraction transformation for hyperspectral image classification [PDF]
, 2017 This paper presents an optimized kernel minimum noise fraction transformation (OKMNF) for feature extraction of hyperspectral imagery. The proposed approach is based on the kernel minimum noise fraction (KMNF) transformation, which is a nonlinear ...
Gao, Lianru +4 more
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Engineering Science and Technology, an International Journal, 2014 Bearing fault, Impeller fault, seal fault and cavitation are the main causes of breakdown in a mono block centrifugal pump and hence, the detection and diagnosis of these mechanical faults in a mono block centrifugal pump is very crucial for its reliable
N.R. Sakthivel +4 more
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Dimensional Reduction of Nonlinear Gauge Theories [PDF]
Journal of High Energy Physics, 2004 20 pages, crucial references ...
Ikeda, Noriaki, Izawa, K. -I.
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Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait [PDF]
, 2010 Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis.
A Arenas +70 more
core +4 more sources