Algorithm design for parallel implementation of the SMC-PHD filter
TLDR
A fully and unbiasedly parallel implementation framework of the SMC-PHD filtering is proposed based on the centralized distributed system that consists of one central unit (CU) and several independent processing elements (PEs).About:
This article is published in Signal Processing.The article was published on 2016-02-01 and is currently open access. It has received 99 citations till now. The article focuses on the topics: Automatic parallelization & Speedup.read more
Citations
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Journal ArticleDOI
How blockchain improves the supply chain: case study alimentary supply chain
Roberto Casado-Vara,Javier Prieto,Fernando De la Prieta,Juan M. Corchado,Juan M. Corchado,Juan M. Corchado +5 more
TL;DR: A new model of supply chain via blockchain via blockchain is proposed, which enables the concept of circular economy and eliminates many of the disadvantages of the current supply chain.
Journal ArticleDOI
A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking
TL;DR: This review examines the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty.
Journal ArticleDOI
Real-time supply chain-A blockchain architecture for project deliveries
Petri Helo,Ahm Shamsuzzoha +1 more
TL;DR: In this paper, the authors proposed a cloud-based portal for real-time tracking and tracing of logistics and supply chains, which is formed by the combination of RFID, IoT and blockchain technology into an integrated realtime view.
Proceedings Article
A particle dyeing approach for track continuity for the SMC-PHD filter
TL;DR: A novel particle labeling method for track continuity for the sequential Monte Carlo (SMC) implementation of the probability hypothesis density (PHD) filter based on observations of successive scans using the Multi-Expected a Posterior (MEAP) estimator.
Book ChapterDOI
Machine Learning Predictive Model for Industry 4.0
Inés Sittón Candanedo,Elena Hernández Nieves,Sara Rodríguez González,M. Teresa Santos Martín,Alfonso González Briones +4 more
TL;DR: The aim of this paper is making use of machine learning algorithms for the design of predictive models in the Industry 4.0 environment, using the previously mentioned HVAC dataset.
References
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Journal ArticleDOI
Multitarget Bayes filtering via first-order multitarget moments
TL;DR: Recursion Bayes filter equations for the probability hypothesis density are derived that account for multiple sensors, nonconstant probability of detection, Poisson false alarms, and appearance, spawning, and disappearance of targets and it is shown that the PHD is a best-fit approximation of the multitarget posterior in an information-theoretic sense.
Journal ArticleDOI
The Gaussian Mixture Probability Hypothesis Density Filter
Ba-Ngu Vo,Wing-Kin Ma +1 more
TL;DR: Under linear, Gaussian assumptions on the target dynamics and birth process, the posterior intensity at any time step is a Gaussian mixture and closed-form recursions for propagating the means, covariances, and weights of the constituent Gaussian components of the posteriorintensity are derived.
Journal ArticleDOI
A Consistent Metric for Performance Evaluation of Multi-Object Filters
TL;DR: This paper outlines the inconsistencies of existing metrics in the context of multi- object miss-distances for performance evaluation, and proposes a new mathematically and intuitively consistent metric that addresses the drawbacks of current multi-object performance evaluation metrics.
Journal ArticleDOI
Sequential Monte Carlo methods for multitarget filtering with random finite sets
TL;DR: In this paper, a sequential Monte Carlo (SMC) multitarget filter is proposed and demonstrated on a number of simulated scenarios, which is suitable for problems involving nonlinear nonGaussian dynamics.
Journal ArticleDOI
PHD filters of higher order in target number
TL;DR: In this article, a closed-form cardinalized probability hypothesis density (CPHD) filter is proposed, which propagates not only the PHD but also the entire probability distribution on target number.