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SVDSingular Value Decomposition
SVDSvenska Dagbladet (Swedish newspaper)
SVDSmall Vessel Disease
SVDSociety of the Divine Word (religious order)
SVDSimultaneous Voice and Data
SVDSwine Vesicular Disease
SVDSimultaneous Voice/Data
SVDSpontaneous Vaginal Delivery
SVDSpontaneous Vertex Delivery (obstetrics)
SVDSelective Vehicle Detection (UK, transportation)
SVDSocietas Verbi Divini (divine word missionaries)
SVDSingle Vision Distance (optometry)
SVDSignature-Verification Data (various organizations)
SVDSt Vincent, St. Vincent And The Grenadines (Airport Code)
SVDStructural Valve Deterioration
SVDSoftware Version Description
SVDSupplementary Volume Descriptor
SVDSoftware Version Document (various organizations)
SVDSubcortical Vascular Dementia
SVDSchweizerische Vereinigung für Datenverarbeitung
SVDSingular Vector Decomposition
SVDSyndicat de la Vente Directe (French: Direct Sales Union)
SVDSpace View Door
SVDSurface Vessel Division
SVDSpace Vehicle Division
SVDStrategic Vision Development
SVDSnowflake Vitreoretinal Degeneration
SVDSegment Version Description
SVDSimplified Vapor Detector
SVDStrategic Vertical Differentiation (industrial economics)
SVDSurveyor Vehicle Department
SVDSmart Vision Device
SVDSnaiperskaia Vintovka Dragunova (Dragunov Sniper Rifle)
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References in periodicals archive ?
Research in Canada showed declines in the LAA subtype and the SVD subtype associated with declines in LDL-C and blood pressure.
In image decomposition by SVD, U and V carry the whole geometric specifications of the image while the luminance is carried by S.
Two main properties, related to the SVs, make the SVD appropriate for watermarking when the matrix S is utilized [8, 22]:
SVD is a typical factorization technology (known as a baseline predictor in some works in the literature).
From this table, we can see that DRBM is faster than these comparing methods, except SVD. NtN and dRW spend a lot of time to compute semantic similarity between GO terms, so they take more time than others.
In this section, we introduce singular value decomposition (SVD) and the removable and robust watermarking scheme proposed by Chang et al.
In this paper a new image enhancement technique based on Singular Wavelet Transform (SWT), Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) has been proposed.
Step 1: Implementing the SVD denoising to filter the original signal and separate the signal of interest from the noise.
For i-th subband apply SVD and get the decomposition [U.sup.*.sub.i] [[SIGMA].sup.*.sub.i] [V.sup.*T.sub.i].
Once the SVD is updated for new samples, the dimension reduction projection matrix and all the parameters {W, [beta], [??]} of SLFN can be updated conveniently
As close as my urban-born SVD friends would be in later life, I became convinced that good ideas and scholarship are insufficient to guide reform and renewal in matters religious.