Results 51 to 60 of about 61,960 (301)
Open Physics, 2017 With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core.
Cui Jia +3 more
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Optimal Intermittent Particle Filter
IEEE Transactions on Signal Processing, 2022 13 pages, 7 figures, 3 ...
Antoine Aspeel +3 more
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Tracking Deformable Object via Particle Filtering on Manifolds
, 2008 Dynamic deformation of target is a prominent problem in image-based tracking. Most existing particle filtering based tracking algorithms treat deformation parameters of the target as a vector.
Shi ZL(史泽林) +5 more
core +1 more source
The Coordinate Particle Filter - a novel Particle Filter for high dimensional systems [PDF]
2015 IEEE International Conference on Robotics and Automation (ICRA), 2015 Parametric filters, such as the Extended Kalman Filter and the Unscented Kalman Filter, typically scale well with the dimensionality of the problem, but they are known to fail if the posterior state distribution cannot be closely approximated by a density of the assumed parametric form.
Manuel Wüthrich +4 more
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A convolution particle filtering approach for tracking elliptical extended objects [PDF]
, 2013 This paper proposes a convolution particle filtering approach for extended object tracking. Convolution particle filters (CPFs) are likelihood free filters. They are based on convolution kernel probability density representation.
Gning, Amadou +3 more
core
Autonomous crowds tracking with box particle filtering and convolution particle filtering [PDF]
Automatica, 2016 Autonomous systems such as Unmanned Aerial Vehicles (UAVs) need to be able to recognise and track crowds of people, e.g. for rescuing and surveillance purposes. Large groups generate multiple measurements with uncertain origin. Additionally, often the sensor noise characteristics are unknown but measurements are bounded within certain intervals.
Allan De Freitas +4 more
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CoRR, 2013 A standard approach to approximate inference in state-space models isto apply a particle filter, e.g., the Condensation Algorithm.However, the performance of particle filters often varies significantlydue to their stochastic nature.We present a class of algorithms, called lattice particle filters, thatcircumvent this difficulty by placing the particles
Dirk Ormoneit +2 more
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Multi-Modal Filtering for Non-linear Estimation [PDF]
, 2014 16.01.14 KB. Ok to add to spiral, authors retain copyrightMulti-modal densities appear frequently in time series and practical applications. However, they are not well represented by common state estimators, such as the Extended Kalman Filter and the ...
Deisenroth, Marc P +11 more
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CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3
Molecular Oncology, EarlyView.PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh +12 more
wiley +1 more source
Multiple particle filtering for tracking wireless agents via Monte Carlo likelihood approximation
EURASIP Journal on Advances in Signal Processing, 2019 The localization of multiple wireless agents via, for example, distance and/or bearing measurements is challenging, particularly if relying on beacon-to-agent measurements alone is insufficient to guarantee accurate localization. In these cases, agent-to-
Stephan Schlupkothen, Gerd Ascheid
doaj +1 more source