In previous studies [20, 21], we proposed extracting the scale effect so as to realize the reductions in complexity per user of SEOD as the number of users increases.
As an enhanced feature detector, the popular scale-invariant feature transform (SIFT) algorithm [12] combines the Harris operator with a staged filtering approach to extract the scale-invariant feature.
The JPEG standard does not define a particular way to do this association it is completely application dependent so that the particular mathematical law used to extract the scaling factor is not important.
To improve the computational speed, Bay et al. [10] introduced the concept of integral images and box filter to detect and extract the scale-invariant features, which they dubbed speeded-up robust features (SURF).
Two components were extracted, and the scale's correlations with the rotated factors were examined [ 28].
From the PCA, one-dominant factor (eigenvalue = 3.529 accounting for 70.6% of variance and covariance in the items) was extracted from the scale items.
DNA was extracted from the scale samples of all guppies initially released in our focal site (Fig. 1), and all individuals were genotyped at 11 microsatellite loci: Pre9, Pre13, Pre15, Pre26, Pre32, Pre38, Pre39, Pre46, Pre53, Pre72, and Pre80 – details of microsatellite amplification are provided elsewhere (Paterson et al. 2005; Crispo et al. 2006).
We briefly discuss the models used in RPES data analysis to extract the time scale of the excited charge delocalisation and the spatial correlation of core, valence occupied and unoccupied molecular states.
We propose to apply PSI approach using high-resolution TSX imagery to extract the regional scale subsidence related to the road network.
In this paper, we propose to apply the persistent scatterer synthetic aperture radar interferometry (PS-InSAR) approach that uses high-resolution TerraSAR-X (TSX) imagery to extract the regional scale subsidence rates (i.e., average annual subsidence in mm/year) along road networks.
