Results 31 to 40 of about 4,661,211 (242)
Box-particle probability hypothesis density filtering [PDF]
, 2014 This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets.
Gning, Amadou +10 more
core +4 more sources
Multi-target Tracking Method Based on GM-PHD Filtering with Weight Constraint [PDF]
Jisuanji gongcheng, 2017 Concerning that the Gaussian Mixture Probability Hypothesis Density(GM-PHD) filter does not check one-to-one assumption and it is difficult to track crossing targets,an improved multi-target tracking method with weight constraint is proposed based on GM ...
ZHAO Yifeng
doaj +1 more source
Cysteine Thioaldehydes: Photolytic Generation, Reactivity, and Biological Implications
Angewandte Chemie, EarlyView.Photolysis of cysteine phenacylsulfides bearing non‐conjugating electron‐withdrawing substituents leads to high conversions into cysteine thioaldehydes through a Norrish type‐II pathway. This methodology enabled the study of the aqueous reactivity of these important biosynthetic intermediates, which, depending on peptide sequence, pH and buffer ...
Ardra Karthika +9 more
wiley +2 more sources
Sensors, 2021 Assuming that the measurement and process noise covariances are known, the probability hypothesis density (PHD) filter is effective in real-time multi-target tracking; however, noise covariance is often unknown and time-varying for an actual scene.
Zhentao Hu +4 more
doaj +1 more source
An Unbalanced Weighted Sequential Fusing Multi-Sensor GM-PHD Algorithm
Sensors, 2019 In this paper, we study the multi-sensor multi-target tracking problem in the formulation of random finite sets. The Gaussian Mixture probability hypothesis density (GM-PHD) method is employed to formulate the sequential fusing multi-sensor GM-PHD (SFMGM-
Han Shen-Tu +4 more
doaj +1 more source
A Robust SMC-PHD Filter for Multi-Target Tracking with Unknown Heavy-Tailed Measurement Noise
Sensors, 2021 In multi-target tracking, the sequential Monte Carlo probability hypothesis density (SMC-PHD) filter is a practical algorithm. Influenced by outliers under unknown heavy-tailed measurement noise, the SMC-PHD filter suffers severe performance degradation.
Yang Gong, Chen Cui
doaj +1 more source
Probability density estimation from optimally condensed data samples [PDF]
, 2003 The requirement to reduce the computational cost of evaluating a point probability density estimate when employing a Parzen window estimator is a well-known problem.
Chao, H., Girolami, M.
core +1 more source
Evidence for a Cu(II)‐Catalysed CuAAC Reaction: A Combined Experimental and Computational Study
Angewandte Chemie, EarlyView.A new mechanistic pathway for the CuAAC reaction has been found to operate under specific reaction conditions. The pathway is catalysed by Cu(II) through a self‐assembled dinuclear Cu(II) complex that incorporates the triazole product. Computational analysis and assessment of generality are reported.
Matthew J. Andrews +12 more
wiley +2 more sources
Conditional density estimation with class probability estimators [PDF]
, 2009 Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty inherent in a prediction. If a conditional density estimate is available, then prediction intervals can be derived from it.
Remco R. Bouckaert +3 more
core +1 more source
Angewandte Chemie, EarlyView.A 310‐helix‐mediated conformational switch promotes a front‐face SNi‐like catalysis by human A4GALT. Mechanism‐guided design identifies AdaGalCer as a selective modulator of globotriaosylceramide (Gb3) biosynthesis, opening a clear route toward new Fabry disease therapeutics.
Nicky de Koster +13 more
wiley +2 more sources