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A DIMENSIONALITY REDUCTION ALGORITHM OF HYPER SPECTRAL IMAGE BASED ON FRACT ANALYSIS
Hyper spectral dimensionality reduction spectral domain fractal analysis feature image
2015/12/30
A dimensionality reduction algorithm based on feature extraction of the spectral curve using fractal analysis which considering both the spatial characteristic and spectral characteristic of hyper spe...
A Systematic Study on the Impact of Dimensionality for a Two-Dimensional Aerodynamic Optimization Model Problem
Systematic Study Impact Dimensionality Two-Dimensional Aerodynamic Optimization Model Problem
2015/7/3
A model problem, based on the NACA0012 airfoil, is studied. The thickness distribution of the symmetric NACA0012 airfoil is optimally approximated with a 4th-order Bezier curve. This best-fit ap...
Characterizing multi-dimensionality of urban sprawl in Jamnagar, India using multi-date remote sensing data
Urban Sprawl Sprawl Metrics GIS Multi-date Remote Sensing Leapfrog development
2014/12/15
This study attempts to measure and characterize urban sprawl using its multiple dimensions in the Jamnagar city, India. The study utilized the multi-date satellite images acquired by CORONA, IRS 1D PA...
A Unified Framework for Dimensionality Reduction and Classification of Hyperspectral Data
Unified Framework SVMDRC Dimensionality Reduction Intrinsic Dimensionality
2014/12/15
The processing of hyperspectral remote sensing data, for information retrieval, is challenging due to its higher dimensionality. Machine learning based algorithms such as Support Vector Machine (SVM) ...
DIMENSIONALITY REDUCTION OF HYPERSPECTRAL IMAGES BY COMBINATION OF NON-PARAMETRIC WEIGHTED FEATURE EXTRACTION (NWFE) AND MODIFIED NEIGHBORHOOD PRESERVING EMBEDDING (NPE)
Hyperspectral Imagery Feature Extraction LDA NPE Classification
2014/12/1
This paper combine two conventional feature extraction methods (NWFE&NPE) in a novel framework and present a new semi-supervised feature extraction method called Adjusted Semi supervised Discriminant ...
DIMENSIONALITY BASED SCALE SELECTION IN 3D LIDAR POINT CLOUDS
point cloud adaptive neighborhood scale selection multi-scale analysis feature PCA eigenvalues dimensionality
2014/6/5
This papers presents a multi-scale method that computes robust geometric features on lidar point clouds in order to retrieve the optimal neighborhood size for each point. Three dimensionality features...
Maximal Linear Embedding for Dimensionality Reduction
Dimensionality reduction manifold learning maximal linear patch landmarks-based global alignment.
2013/7/24
Over the past few decades, dimensionality reduction has been widely exploited in computer vision and pattern analysis.This paper proposes a simple but effective nonlinear dimensionality reduction algo...
On Three-Dimensionality of Turbulent Buoyant Channel Flow
Buoyancy Channel flow Turbulence
2010/1/14
A three-dimensional buoyancy-driven turbulent boundary layer is generated in fully developed turbulent channel flow.
Setting the buoyancy forces perpendicular to the mean flow direction and using hig...
High-Tc Superconducting Electronics: Implications of Reduced Dimensionality
High-Tc Superconducting Electronics Reduced Dimensionality the superconducting state
2010/12/16
First, we present experimental evidence that Bi-Sr-Ca-Cu-O superconductors are effectively quasi-two dimensional, in both the normal and the superconducting state. Next, we analyze how this unusual pr...