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A probabilistic particle tracking framework for guided and Brownian motion systems with high particle densities

This paper presents a new framework for particle tracking based on a Gaussian Mixture Model (GMM). It is an extension of the state-of-the-art iterative reconstruction of individual particles by a continuous modeling of the particle trajectories considering the position and velocity as coupled quantities.…
Singapore: Springer Singapore, 2021-10-17

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