Title Multisensor fusion and integration in the wake of big data, deep learning and cyber physical system : an edition of the selected papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017) / Sukhan Lee, Hanseok Ko, Songhwai Oh, editors

Published Cham, Switzerland : Springer, 2018

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Description 1 online resource Series Lecture notes in electrical engineering, 1876-1100 ; volume 501 Lecture notes in electrical engineering ; v. 501. Contents Intro; Preface; Contents; Multi-sensor Fusion: Theory and Practice; Covariance Projection as a General Framework of Data Fusion and Outlier Removal; Abstract; 1 Introduction; 1.1 Problem Statement; 2 Proposed Approach; 3 Confidence Measure of Data Sources; 3.1 Inconsistency Detection and Exclusion; 3.2 Effect of Correlation on d Distance; 4 Simulation Results; 5 Conclusion; Acknowledgments; Appendix 1; Appendix 2; References; State Estimation in Networked Control Systems with Delayed and Lossy Acknowledgments; 1 Introduction; 2 Problem Formulation; 3 Derivation of the Proposed Estimator 3.1 Modeling the NCS as a Markov Jump Linear System3.2 Estimator Design; 4 Evaluation; 5 Conclusions; References; Performance of State Estimation and Fusion with Elliptical Motion Constraints; 1 Introduction; 2 System Model; 2.1 Coordinated Turn (CT) Model; 2.2 Elliptical Constraint; 2.3 Generating Constrained States; 3 Projection-Based Constrained Estimation; 3.1 Direct Connection to Ellipse Center; 3.2 Shortest Distance to Unconstrained Estimate; 4 Fusion of Constrained Estimates; 4.1 Fusion Rules; 4.2 Fusion Rules with Constrained Estimates; 5 Constrained Fusion with Information Loss 5.1 Simulation Setup5.2 Performance; 6 Conclusions; References; Relevance and Redundancy as Selection Techniques for Human-Autonomy Sensor Fusion; 1 Introduction; 2 Related Work; 3 Theory and Background; 3.1 Preliminaries; 3.2 Relevance; 3.3 Redundancy; 3.4 Relevance and Redundancy with Specific Fusion Algorithms; 4 Empirical Tests; 4.1 Redundancy; 4.2 Relevance; 4.3 Redundancy vs. Relevance; 5 Conclusions and Future Work; References; Classification of Reactor Facility Operational State Using SPRT Methods with Radiation Sensor Networks; 1 Introduction; 2 Detection Problem; 2.1 SPRT Detection 2.2 Stack Intensity Estimation3 IRSS Experimental Results; 3.1 IRSS Datasets; 3.2 Experimental SPRTs; 3.3 Performance Comparison; 4 HFIR Experimental Results; 4.1 HFIR Datasets and Experimental SPRTs; 4.2 Performance Comparison; 5 Performance of IE SPRT Detection Method; 5.1 Single Location Measurements; 5.2 Network Measurements; 6 Conclusion; References; Improving Ego-Lane Detection by Incorporating Source Reliability; 1 Introduction; 2 Related Work; 2.1 Multi-source Fusion for Ego-Lane Detection; 2.2 Reliability in Fusion; 3 Concept of Reliability-Aware Ego-Lane Detection 4 Reliability for Ego-Lane Detection4.1 Requirements; 4.2 Sensor-Independent Performance Measure; 5 Learning Reliabilities of Ego-Lane Estimations; 5.1 Learning Reliability Using Classifiers; 5.2 Training Data for the Classifiers; 5.3 Feature Selection; 5.4 Applying Classifiers Towards Learning Reliability; 6 Reliability-Aware Ego-Lane Fusion; 6.1 Dempster-Shafer Theory (DST):; 6.2 Other Fusion Approaches; 7 Experimental Evaluation; 7.1 Assessment of Reliability Estimation; 7.2 Assessment Information Fusion; 7.3 Exemplary Results; 8 Conclusion; References Summary This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16-22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories Notes Includes author index Online resource; title from PDF title page (SpringerLink, viewed July 13, 2018) Subject Multisensor data fusion -- Congresses Intelligent control systems -- Congresses Big data -- Congresses Cooperating objects (Computer systems) -- Congresses Artificial intelligence. Robotics. Communications engineering -- telecommunications. COMPUTERS -- General. Big data Cooperating objects (Computer systems) Intelligent control systems Multisensor data fusion Genre/Form Conference papers and proceedings proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès. Form Electronic book Author Lee, Sukhan, editor Ko, Hanseok, editor. Oh, Songhwai, editor ISBN 9783319905099 3319905090

Other Titles MFI 2017

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