Advances in Multi-Sensor Information Fusion : : Theory and Applications 2017 / / edited by Xue-Bo Jin [and three others].

• TeilnehmendeR: Jin, Xue-Bo,
• Place / Publishing House: Basel, Switzerland : : MDPI - Multidisciplinary Digital Publishing Institute,, [2018]; ©2018
• Year of Publication: 2018
• Language: English
• Physical Description: 1 online resource (620 pages) :; illustrations

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time...

Table of Contents

• About the Special Issue Editors
• Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
• Facial Expression Recognition with Fusion Features Extracted from Salient Facial Areas
• Object Tracking Using Local Multiple Features and a PosteriorProbability Measure
• Strong Tracking Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking
• Random Finite Set Based Bayesian Filtering with OpenCL in a Heterogeneous Platform
• State Estimation Using Dependent Evidence Fusion: Application to Acoustic ResonanceBased Liquid Level Measurement
• Auxiliary Truncated Unscented Kalman Filtering for Bearings-Only Maneuvering Target Tracking
• Flexible Fusion Structure-Based Performance OptimizationLearning for Multisensor Target Tracking
• Development of Data Registration and Fusion Methods for Measurement of Ultra-Precision Freeform Surfaces
• Optimal Fusion Estimation with Multi-Step Random Delays and Losses in Transmission
• Multisensor Parallel Largest Ellipsoid Distributed Data Fusion with Unknown Cross-Covariance
• A Reliability-Based Method to Sensor Data Fusion
• Online Denoising Based on the Second-Order Adaptive Statistics Model
• A Time-Space Domain Information Fusion Method for Specific Emitter Identification Based on Dempster-Shafer Evidence Theory
• Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method
• Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information
• A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles
• An Improved Evidential-IOWA Sensor Data Fusion Approach in Fault Diagnosis
• Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks
• Tracking of Maneuvering Complex Extended Object with Coupled Motion Kinematics and Extension Dynamics Using Range Extent Measurements
• A Clustering-Oriented Closeness Measure Based on Neighborhood Chain and Its Application in the Clustering Ensemble Framework Based on the Fusion of Different Closeness Measures
• A Weighted Measurement Fusion Particle Filter for Nonlinear Multisensory Systems Based on Gauss-Hermite Approximation
• Cooperative Localization for Multi-AUVs Based on GM-PHD Filters and Information Entropy Theory
• Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient
• A Novel Evidence Theory and Fuzzy Preference Approach-Based Multi-Sensor Data Fusion Technique for Fault Diagnosis
• Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association
• Integrated Display and Simulation for Automatic Dependent Surveillance-Broadcast and Traffic Collision Avoidance System Data Fusion
• Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertaintie
• IMU-Based Gait Recognition Using Convolutional Neural Networks and Multi-Sensor Fusion
• Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Network
• A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data.