Multi-Sensor Information Fusion

This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, esti...

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Hlavní autoři:	Gao, Yuan, Jin, Xue-Bo
Médium:	Online
Jazyk:	angličtina
Vydáno:	MDPI - Multidisciplinary Digital Publishing Institute 2021
Témata:	TA1-2040 T1-995 similarity measure information filter out-of-sequence Hellinger distance coefficient of determination maximization strategy uncertainty measure embedded systems Internet of things (IoT) random delays adaptive distance function random finite set Dempster–Shafer evidence theory (DST) safe trajectory health reliability degree dynamic optimization state probability approximation sensors bias multi-environments belief entropy quaternion closed world Gaussian process regression Gaussian mixture model (GMM) intelligent transport system multirotor UAV multi-sensor system attitude time-domain data fusion precision landing Industry 4.0 magnetic angular rate and gravity (MARG) sensor uncertainty unscented information filter data classification high-definition map global information inconsistent data extended belief entropy sensor system Steffensen’s iterative method SLAM the Range-Range-Range frame evidential reasoning belief functions powered two wheels (PTW) electronic nose particle swarm optimization grey group decision-making user experience platform complex surface measurement DoS attack extended Kalman filter ICP Gaussian density peak clustering artificial marker random parameter matrices optimal estimate local structure descriptor object classification domain adaption networked systems expectation maximization (EM) algorithm attitude estimation Gaussian process model least-squares smoothing target positioning RFS spectral clustering maintenance decision multi-target tracking GMPHD time-distributed ConvLSTM model non-rigid feature matching unknown inputs cardiac PET subspace alignment gradient domain multi-sensor measurement data fusion Bar-Shalom Campo Kalman filter signal feature extraction methods sensor data fusion algorithm distributed architecture predictive modeling techniques Gaussian mixture model self-reporting deep learning mutual support degree security zones sensor array soft sensor aircraft pilot projection vehicle-to-everything distributed intelligence system square-root cubature Kalman filter information fusion evidence combination LiDAR feature representations multi-sensor information fusion linear constraints galvanic skin response decision-level sensor fusion most suitable parameter form Pignistic vector angle SINS/DVL integrated navigation fault diagnosis facial expression yaw estimation dual gating multi-sensor data fusion multisensor system A* search algorithm data fusion architectures drift compensation augmented state Kalman filtering (ASKF) manifold nested iterative method data preprocessing interference suppression conflicting evidence sonar network Gaussian process health management decision state estimation eye-tracking high-dimensional fusion data (HFD) MEMS accelerometer and gyroscope multitarget tracking gaussian mixture probability hypothesis density integer programming image registration Dempster–Shafer evidence theory linear regression data association nonlinear system covariance matrix multi-source data fusion fuzzy neural network least-squares filtering fire source localization network flow theory weight maps camera plane matching calibration unmanned aerial vehicle fixed-point filter workload intelligent and connected vehicles mimicry security switch strategy alumina concentration the Range-Point-Range frame spatiotemporal feature learning distributed fusion user experience evaluation image fusion vehicular localization sensor fusion vibration parameter learning weighted fusion estimation data registration pose estimation surface quality control trajectory reconstruction land vehicle square root Deng entropy multi-focus EEG low-cost sensors sensor fusing sensor data fusion packet dropouts estimation industrial cyber-physical system (ICPS) multi-sensor time series multi-sensor network Human Activity Recognition (HAR) transfer multisensor data fusion convergence condition interaction tracker acoustic emission Covariance Projection method mix-method approach orthogonal redundant inertial measurement units sematic segmentation Surface measurement conflict measurement user experience measurement observable degree analysis open world novel belief entropy cutting forces machine health monitoring Bayesian reasoning method orientation surface modelling hybrid adaptive filtering supervoxel RTS smoother Dempster-Shafer evidence theory (DST) fast guided filter. multi-sensor joint calibration principal component analysis thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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Popis
Shrnutí:	This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

Multi-Sensor Information Fusion

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