Results 11 to 20 of about 5,912,392 (297)
Kernel Density Estimation: a novel tool for visualising training intensity distribution in biathlon. [PDF]
Front Sports Act 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
Staunton CA +4 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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Multivariate kernel density estimation with a parametric support [PDF]
Opuscula Mathematica, 2009 We consider kernel density estimation in the multivariate case, focusing on the use of some elements of parametric estimation. We present a two-step method, based on a modification of the EM algorithm and the generalized kernel density estimator, and ...
Jolanta Jarnicka
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Ecosphere, 2021 Accurate population estimates are essential for monitoring and managing wildlife populations. Mark–recapture sampling methods have regularly been used to estimate population parameters for rare and cryptic species, including the federally listed Mojave ...
Corey I. Mitchell +7 more
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IEEE Access, 2021 The most pervasive segment of techniques in managing class imbalance in machine learning are re-sampling-based methods. The emergence of deep generative models for augmenting the size of the under-represented class, prompts one to review the question of ...
Behroz Mirza +4 more
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Interpretability With Accurate Small Models
Frontiers in Artificial Intelligence, 2020 Models often need to be constrained to a certain size for them to be considered interpretable. For example, a decision tree of depth 5 is much easier to understand than one of depth 50. Limiting model size, however, often reduces accuracy.
Abhishek Ghose, Balaraman Ravindran
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Sheep Counting Method Based on Multiscale Module Deep Neural Network
IEEE Access, 2022 Due to the uneven distribution and large scale change of sheep in the pasture, it is not conducive to the counting and statistics of sheep in animal husbandry.
Jianming Xu +3 more
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Rapid dung removal by beetles suggests higher duiker densities in Central African rainforests
Oryx, 2023 For many mammal species, converting dung density into population density requires accurate estimates of defaecation rate and dung survival time. The latter parameter probably varies seasonally.
Towa Olivier William Kamgaing +4 more
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Cascaded Multi-Task Learning of Head Segmentation and Density Regression for RGBD Crowd Counting
IEEE Access, 2020 In this paper we propose a novel regression based RGBD crowd counting method. Compared with previous RGBD crowd counting methods which mainly exploit depth cue to facilitate person/head detection, our approach adopts density map regression and is more ...
Desen Zhou, Qian He
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Analysis of KNN Density Estimation [PDF]
IEEE Transactions on Information Theory, 2020 We analyze the convergence rates of $k$ nearest neighbor density estimation method, under $\ell _{\alpha} $ norm with $\alpha \in [1,\infty]$ . Our analysis includes two different cases depending on whether the support set is bounded or not.
Puning Zhao, L. Lai
semanticscholar +1 more source