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List of Tutorials of FUSION 2016 T1 Bayesian Multiple Target Tracking T2 Bayesian Networks and Trust Fusion with Subjective Logic T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter T5 A Finite-Set Statistics Prime T6 Information Quality in Information Fusion and Decision Making T7 Multitarget Tracking and Multisensor Information Fusion T8 Overview of High-Level Information Fusion Theory, Models, and Representations T9 Quantum Physics Methods For Nonlinear Filtering T10 Basic concepts in multiobject estimation T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion T12 Implementations of random-finite-set-based multi-target filters T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications T14 Multistatic Exploration – Introduction to Modern Patutoialive Radar and Multistatic Tracking & Data Fusion T15 Big Data Fusion and Analytics T16 Object tracking, sensor fusion and situational awarenetutoial for atutoialisted- and self-driving vehicles: Problems, solutions and directions T17 Emerging Quantum Technologies for Fusion T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods T19 Integration of Information to Indentify Objects in Big Data T20 Extended Object Tracking: Theory and Applications T21 Probabilistic situation atutoialetutoialment for abnormal interaction detection T22 Multitarget tracking and sensor calibration in centralized and distributed networks T23 Information fusion in resource-limited camera networks T24 Introduction to Bayesian Filtering and Smoothing T25 Sensor Fusion for Intelligent Vehicles T26 Sensor Fusion for Intelligent Vehicles

T1 Bayesian Multiple Target Tracking Presenter:

T2 Bayesian Networks and Trust Fusion with Subjective Logic Presenter:

T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios Presenter:

T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter Presenter:

T5 A Finite-Set Statistics Prime Presenter:

T6 Information Quality in Information Fusion and Decision Making Presenter:

T7 Multitarget Tracking and Multisensor Information Fusion Presenter:

T8 Overview of High-Level Information Fusion Theory, Models, and Representations Presenter:

T9 Quantum Physics Methods For Nonlinear Filtering Presenter:

T10 Basic concepts in multiobject estimation Presenter:

T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion Presenter:

T12 Implementations of random-finite-set-based multi-target filters Presenter:

T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications Presenter:

T14 Multistatic Exploration – Introduction to Modern Patutoialive Radar and Multistatic Tracking & Data Fusion Presenter:

T15 Big Data Fusion and Analytics Presenter:

T16 Object tracking, sensor fusion and situational awarenetutoial for atutoialisted- and self-driving vehicles: Problems, solutions and directions Presenter:

T17 Emerging Quantum Technologies for Fusion Presenter:

T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods Presenter:

T19 Integration of Information to Identify Objects in Big Data Presenter:

T20 Extended Object Tracking: Theory and Applications Presenter:

T21 Probabilistic situation assessment for abnormal interaction detection Presenter:

T22 Multitarget tracking and sensor calibration in centralized and distributed networks Presenter:

T23 Information fusion in resource-limited camera networks Presenter:

T24 Introduction to Bayesian Filtering and Smoothing Presenter:

T25 Sensor Fusion for Intelligent Vehicles Presenter:

T26 Multisensor Data Fusion in Shared Sensor and Actuator Networks Presenter: