Depth-based multivariate descriptive statistics with hydrological applications

Instead of directly encoding the light field (the array of sub-aperture images or the lenslet image for light fields cap- tured by plenoptic cameras), the authors in [13] consider

Dieses instruktive und ansprechend gestaltete Buch bietet nicht nur eine auf Archiv-Recherchen basierende Studie über die Entstehungsgeschichte der Vita D[omi]ni n[ost]ri Jesu

Depth functions for multivariate data have been pursued in nonparametric data analysis and robust inference [15]. Depth functions assign to each point its degree of centrality with

Au- thors propose a two-step pose estimation algorithm where two different networks are trained, one for image retrieval by deep descriptor indexing and a second pose refinement step

Compared to the decision metric previously proposed by Premus and Helfrick, 3 the main difference is that energy ratio is here computed in mode space, whereas they use projections

This approach is based on our preceding works [6, 16] on the Bercovici-Pata bijection (see also [7, 26, 10]). This bijection, that we denote by Λ, is a correspondence between

do compare favourable to those eluded from the Ames test analysis, the observations that the highly genotoxic CAFs and mutagenic DEPs, as well as the SWCNTs and MWCNTs cause a

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