Results 21 to 30 of about 11,537 (265)
Knowledge Transfer Based on Particle Filters for Multi-Objective Optimization
Mathematical and Computational Applications, 2023 Particle filters, also known as sequential Monte Carlo (SMC) methods, constitute a class of importance sampling and resampling techniques designed to use simulations to perform on-line filtering.
Xilu Wang, Yaochu Jin
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SKELETONIZATION WITH PARTICLE FILTERS [PDF]
International Journal of Pattern Recognition and Artificial Intelligence, 2010 We present a novel method to obtain high quality skeletons of binary shapes. The obtained skeletons are connected and one pixel thick. They do not require any pruning or any other post-processing. The computation is composed of two major parts. First, a small set of salient contour points is computed.
Yuchun Tang +5 more
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Particle Filter Based on Harris Hawks Optimization Algorithm for Underwater Visual Tracking
Journal of Marine Science and Engineering, 2023 Due to the complexity of the underwater environment, tracking underwater targets via traditional particle filters is a challenging task. To resolve the problem that the tracking accuracy of a traditional particle filter is low due to the sample ...
Junyi Yang, Yutong Yao, Donghe Yang
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Buildings, 2021 Air filters are crucial components of a building ventilation system that contribute to improving indoor air quality, but they are typically associated with relatively high pressure drops. The purpose of the study is to evaluate the effect of additives on
Roberta Orlando +4 more
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A Local Particle Filter Using Gamma Test Theory for High‐Dimensional State Spaces
Journal of Advances in Modeling Earth Systems, 2020 Particle filters are non‐Gaussian filters, which means that the assumption that the error distribution of the ensemble should be Gaussian is unnecessary.
Zhenwu Wang +2 more
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Nudging the particle filter [PDF]
Statistics and Computing, 2019 AbstractWe investigate a new sampling scheme aimed at improving the performance of particle filters whenever (a) there is a significant mismatch between the assumed model dynamics and the actual system, or (b) the posterior probability tends to concentrate in relatively small regions of the state space.
Ömer Deniz Akyildiz, Joaquín Míguez
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Multiple object tracking using particle filters [PDF]
, 2006 The particle filtering technique with multiple cues such as colour, texture and edges as observation features is a powerful technique for tracking deformable objects in image sequences with complex backgrounds.
N. Canagarajah +11 more
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Atmospheric Environment: X, 2020 The enforcement of more stringent type approval emission standards de facto mandate manufacturers to equip vehicles with particle filters, which reduces the particle number concentration in automotive emissions to levels below typical ambient ...
Markus Bainschab +2 more
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Exact approximation of Rao-Blackwellised particle filters [PDF]
, 2012 Particle methods are a category of Monte Carlo algorithms that have become popular for performing inference in non-linear non-Gaussian state-space models.
Dancer, R. +7 more
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