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Kernel Density Estimation: a novel tool for visualising training intensity distribution in biathlon [PDF]
Frontiers in Sports and Active LivingPurposeThis study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how KDE plots, alongside traditional training metrics, might
Craig A. Staunton +7 more
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DEMANDE: Density Matrix Neural Density Estimation
IEEE Access, 2023 Density estimation is a fundamental task in statistics and machine learning that aims to estimate, from a set of samples, the probability density function of the distribution that generated them.
Joseph A. Gallego-Mejia +1 more
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Scale and Background Aware Asymmetric Bilateral Network for Unconstrained Image Crowd Counting
Mathematics, 2022 This paper attacks the two challenging problems of image-based crowd counting, that is, scale variation and complex background. To that end, we present a novel crowd counting method, called the Scale and Background aware Asymmetric Bilateral Network ...
Gang Lv +4 more
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Remote Sensing in Ecology and Conservation, 2022 Accurate and precise density estimates are crucial for effective species management and conservation. However, efficient monitoring of mammal densities over large spatial and temporal scales is challenging.
Samantha S. Mason +5 more
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BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures
Journal of Statistical Software, 2021 BNPmix is an R package for Bayesian nonparametric multivariate density estimation, clustering, and regression, using Pitman-Yor mixture models, a flexible and robust generalization of the popular class of Dirichlet process mixture models.
Riccardo Corradin +2 more
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Applied Sciences, 2022 We consider the use of remote sensing for large-scale monitoring of agricultural land use, focusing on classification of tillage and vegetation cover for individual field parcels across large spatial areas.
Markku Luotamo +2 more
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Improved Initialization of the EM Algorithm for Mixture Model Parameter Estimation
Mathematics, 2020 A commonly used tool for estimating the parameters of a mixture model is the Expectation−Maximization (EM) algorithm, which is an iterative procedure that can serve as a maximum-likelihood estimator.
Branislav Panić +2 more
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Estimating snow leopard and prey populations at large spatial scales
Ecological Solutions and Evidence, 2021 Effective management of charismatic large carnivores requires robust monitoring of their population at local, regional and global scales. While enormous progress has been made to estimate carnivore populations at local scales, estimates at regional and ...
Kulbhushansingh Suryawanshi +11 more
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Estimating insect pest density using the physiological index of crop leaf
Frontiers in Plant Science, 2023 Estimating population density is a fundamental study in ecology and crop pest management. The density estimation of small-scale animals, such as insects, is a challenging task due to the large quantity and low visibility. An herbivorous insect is the big
Meng Chen, Xiang-Dong Liu
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Admissible predictive density estimation [PDF]
, 2008 Let $X|\mu\sim N_p(\mu,v_xI)$ and $Y|\mu\sim N_p(\mu,v_yI)$ be independent $p$-dimensional multivariate normal vectors with common unknown mean $\mu$. Based on observing $X=x$, we consider the problem of estimating the true predictive density $p(y|\mu ...
Brown, Lawrence D. +2 more
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