Results 71 to 80 of about 114,723 (161)

Euclidean distance-optimized data transformation for cluster analysis in biomedical data (EDOtrans). [PDF]

BMC Bioinformatics, 2022
Ultsch A, Lötsch J.
europepmc   +1 more source

Estimating Euclidean Distance to Linearity.

Given oracle access to a real-valued function on the n-dimensional Boolean cube, how many queries does it take to estimate the squared Euclidean distance to its closest linear function within ε? Our main result is that O(log³(1/ε) ⋅ 1/ε²) queries suffice.
Bogdanov, Andrej, Taschin, Lorenzo
openaire   +3 more sources

An Indoor Navigation Algorithm Using Multi-Dimensional Euclidean Distance and an Adaptive Particle Filter. [PDF]

Sensors (Basel), 2021
Hu Y, Peng A, Tang B, Xu H.
europepmc   +1 more source

Multidimensional Minimum Euclidean Distance Approach Using Radar Reflectivities for Oil Slick Thickness Estimation. [PDF]

Sensors (Basel), 2022
Hammoud B, Daou G, Wehn N.
europepmc   +1 more source

Subcellular Euclidean distance measurements with multicolor fluorescence localization imaging in cultured cells. [PDF]

STAR Protoc, 2021
Germanova TE, Roscioli E, Harrison JU, McAinsh AD, Burroughs NJ.   +4 more
europepmc   +1 more source

Weighted assignment fusion algorithm of evidence conflict based on Euclidean distance and weighting strategy, and application in the wind turbine system. [PDF]

PLoS One, 2022
Gou L, Zhang J, Li N, Wang Z, Chen J, Qi L.   +5 more
europepmc   +1 more source

Estimation and construction of confidence intervals for biomarker cutoff-points under the shortest Euclidean distance from the ROC surface to the perfection corner. [PDF]

Stat Med, 2021
Mosier BR, Bantis LE.
europepmc   +1 more source

The Euclidean distance degree of Fermat hypersurfaces

Journal of Symbolic Computation, 2017
Finding the point in an algebraic variety that is closest to a given point is an optimization problem with many applications. We study the case when the variety is a Fermat hypersurface. Our formula for its Euclidean distance degree is a piecewise polynomial whose pieces are defined by subtle congruence conditons.
openaire   +2 more sources

Accelerating Euclidean Distance Transforms: A Fast and Flexible Approach With Multi-Vendor GPU, Multi-Threading, and Multi-Language Support

IEEE Access
Euclidean distance transforms are fundamental in image processing and computer vision, with critical applications in medical image analysis and computer graphics.
Dale Black, Wenbo Li, Qiyu Zhang, Sabee Molloi   +3 more
doaj   +1 more source

A novel methodological framework for predicting and mapping agriculture-related soil attributes using Euclidean distance, regular grids, and machine learning algorithms. [PDF]

PLoS One
Veloso GV, de Mello DC, Fernandes-Filho EI, de Souza CMP, da Silva LAP, Santo MME, Vasques GM, Coelho MR, Demattê JAM.   +8 more
europepmc   +1 more source