Results 11 to 20 of about 8,023,314 (274)
Dimensionality Reduction with Image Data [PDF]
, 2004 A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We propose a new method based on the projection of the images as matrices after a Procrustes rotation and show that it leads to a better reconstruction of images.
Peña, Daniel, Benito, Mónica
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Shape-aware stochastic neighbor embedding for robust data visualisations
BMC Bioinformatics, 2022 Background The t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm has emerged as one of the leading methods for visualising high-dimensional (HD) data in a wide variety of fields, especially for revealing cluster structure in HD single-cell ...
Tobias Wängberg +2 more
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DIMENSIONAL REDUCTION ON A SPHERE [PDF]
International Journal of Modern Physics B, 2006 The question of the dimensional reduction of two-dimensional (2d) quantum models on a sphere to one-dimensional (1d) models on a circle is addressed. A possible application is to look at a relation between the 2d anyon model and the 1d Calogero–Sutherland model, which would allow for a better understanding of the connection between 2d anyon exchange ...
Moller, Gunnar +2 more
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Dimensionality reduction using singular vectors
Scientific Reports, 2021 A common problem in machine learning and pattern recognition is the process of identifying the most relevant features, specifically in dealing with high-dimensional datasets in bioinformatics.
Majid Afshar, Hamid Usefi
doaj +1 more source
Dimensionality reduction in Bayesian estimation algorithms [PDF]
Atmospheric Measurement Techniques, 2013 An idealized synthetic database loosely resembling 3-channel passive microwave observations of precipitation against a variable background is employed to examine the performance of a conventional Bayesian retrieval algorithm.
G. W. Petty
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Dimensionality Reduction in Surrogate Modeling: A Review of Combined Methods
Data Science and Engineering, 2022 Surrogate modeling has been popularized as an alternative to full-scale models in complex engineering processes such as manufacturing and computer-assisted engineering.
Chun Kit Jeffery Hou, K. Behdinan
semanticscholar +1 more source
Dimensional reduction in the sky [PDF]
Physical Review D, 2013 We explore the cosmological implications of a mechanism found in several approaches to quantum-gravity, whereby the spectral dimension of spacetime runs from the standard value of 4 in the infrared (IR) to a smaller value in the ultraviolet (UV). Specifically, we invoke the picture where the phenomenon is associated with modified dispersion relations ...
João Magueijo +4 more
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Deformed dimensional reduction
Geometry & Topology, 2022 Since its first use by Behrend, Bryan, and Szendrői in the computation of motivic Donaldson-Thomas (DT) invariants of $\mathbb{A}_{\mathbb{C}}^3$, dimensional reduction has proved to be an important tool in motivic and cohomological DT theory. Inspired by a conjecture of Cazzaniga, Morrison, Pym, and Szendrői on motivic DT invariants, work of ...
Davison, Ben, Pădurariu, Tudor
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Dimensionality Reduction and Classification of Hyperspectral Remote Sensing Image Feature Extraction
Remote Sensing, 2022 Terrain classification is an important research direction in the field of remote sensing. Hyperspectral remote sensing image data contain a large amount of rich ground object information.
Hongda Li +4 more
semanticscholar +1 more source
On the dimensional reduction procedure [PDF]
Nuclear Physics B, 2001 15 pages, Latex, enlarged discussion added in Sec 3 and typos corrected. Version to appear in Nucl.
Cognola, Guido, Zerbini, Sergio
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