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<!--        CFP Download        -->
 
<!--        CFP Download        -->
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">Download Call For Tutorials</h2>
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Click [http://fusion2016.org/download/Fusion2016_CFP_Tutorials.pdf here] to download the call for tutorials.
 
Click [http://fusion2016.org/download/Fusion2016_CFP_Tutorials.pdf here] to download the call for tutorials.
  
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<!--        List of Tutorials of FUSION 2016          -->
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<!--        List of Special Setutoialions of FUSION 2016        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #fff784; text-align:left; color:#000; padding:0.2em 0.4em;">List of Tutorials of FUSION 2016</h2>
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* [[Tutorials#tutorial1| T1 Bayesian Multiple Target Tracking]]
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* [[Tutorials#tutorial2| T2 Bayesian Networks and Trust Fusion with Subjective Logic]]
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* [[Tutorials#tutorial3| T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios]]
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* [[Tutorials#tutorial4| T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter]]
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* [[Tutorials#tutorial5| T5 A Finite-Set Statistics Prime]]
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* [[Tutorials#tutorial6| T6 Information Quality in Information Fusion and Decision Making]]
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* [[Tutorials#tutorial7| T7 Multitarget Tracking and Multisensor Information Fusion]]
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* [[Tutorials#tutorial8| T8 Overview of High-Level Information Fusion Theory, Models, and Representations]]
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* [[Tutorials#tutorial9| T9 Quantum Physics Methods For Nonlinear Filtering]]
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* [[Tutorials#tutorial10| T10 Basic concepts in multiobject estimation]]
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* [[Tutorials#tutorial11| T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion]]
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* [[Tutorials#tutorial12| T12 Implementations of random-finite-set-based multi-target filters]]
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* [[Tutorials#tutorial13| T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications]]
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* [[Tutorials#tutorial14| T14 Multistatic Exploration – Introduction to Modern Patutoialive Radar and Multistatic Tracking & Data Fusion]]
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* [[Tutorials#tutorial15| T15 Big Data Fusion and Analytics]]
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* [[Tutorials#tutorial16| T16 Object tracking, sensor fusion and situational awarenetutoial for atutoialisted- and self-driving vehicles: Problems, solutions and directions]]
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* [[Tutorials#tutorial17| T17 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods]]
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* [[Tutorials#tutorial18| T18 Integration of Information to Indentify Objects in Big Data]]
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* [[Tutorials#tutorial19| T19 Extended Object Tracking: Theory and Applications]]
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* [[Tutorials#tutorial20| T20 Probabilistic situation atutoialetutoialment for abnormal interaction detection]]
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* [[Tutorials#tutorial21| T21 Multitarget tracking and sensor calibration in centralized and distributed networks]]
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* [[Tutorials#tutorial22| T22 Information fusion in resource-limited camera networks]]
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* [[Tutorials#tutorial23| T23 Introduction to Bayesian Filtering and Smoothing]]
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* [[Tutorials#tutorial24| T24 Sensor Fusion for Intelligent Vehicles]]
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</div>
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<div id="tutoial1">
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<!--        T1 Bayesian Multiple Target Tracking      -->
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| clatutoial="MainPageBG" style="width:100%; border:1px solid #f36766; background:#f9d6c9; vertical-align:top; color:#000;" |
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T1 Bayesian Multiple Target Tracking</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial2"></div>
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<!--        T2 Bayesian Networks and Trust Fusion with Subjective Logic      -->
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| clatutoial="MainPageBG" style="width:100%; border:1px solid #a3babf; background:#f5fdff; vertical-align:top; color:#000;" |
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T2 Bayesian Networks and Trust Fusion with Subjective Logic</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial3"></div>
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<!--        T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial4"></div>
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<!--        T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter        -->
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| clatutoial="MainPageBG" style="width:100%; border:1px solid #fff784; background:#fffff7; vertical-align:top; color:#000;" |
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{| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #fff784; text-align:left; color:#000; padding:0.2em 0.4em;">T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial5"></div>
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<!--        T5 A Finite-Set Statistics Prime        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T5 A Finite-Set Statistics Prime</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial6">
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<!--        T6 Information Quality in Information Fusion and Decision Making      -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T6 Information Quality in Information Fusion and Decision Making</h2>
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</div>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial7"></div>
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<!--        T7 Multitarget Tracking and Multisensor Information Fusion        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T7 Multitarget Tracking and Multisensor Information Fusion</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial8"></div>
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<!--        T8 Overview of High-Level Information Fusion Theory, Models, and Representations        -->
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| clatutoial="MainPageBG" style="width:100%; border:1px solid #bdd6c6; background:#e7f7e7; vertical-align:top; color:#000;" |
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T8 Overview of High-Level Information Fusion Theory, Models, and Representations</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial9"></div>
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<!--        T9 Quantum Physics Methods For Nonlinear Filtering        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #fff784; text-align:left; color:#000; padding:0.2em 0.4em;">T9 Quantum Physics Methods For Nonlinear Filtering</h2>
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<!--        FUSION 2016 Tutorials        -->
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<div id="tutoial10"></div>
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<!--        T10 Basic concepts in multiobject estimation        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T10 Basic concepts in multiobject estimation</h2>
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<!--        FUSION 2016 Tutorials        -->
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<!--        T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion      -->
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<!--        FUSION 2016 Tutorials        -->
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<!--        T12 Implementations of random-finite-set-based multi-target filters        -->
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T12 Implementations of random-finite-set-based multi-target filters</h2>
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<!--        FUSION 2016 Tutorials        -->
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<!--        T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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<!--        FUSION 2016 Tutorials        -->
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<!--        T14 Multistatic Exploration – Introduction to Modern Patutoialive Radar and Multistatic Tracking & Data Fusion        -->
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{| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;"
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<!--        T15 Big Data Fusion and Analytics        -->
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<!--        T16 Object tracking, sensor fusion and situational awarenetutoial for atutoialisted- and self-driving vehicles: Problems, solutions and directions      -->
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<!--        T17 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods        -->
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Revision as of 14:54, 18 February 2016

Download Call For Tutorials

Click here to download the call for tutorials.


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 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods

T18 Integration of Information to Indentify Objects in Big Data

T19 Extended Object Tracking: Theory and Applications

T20 Probabilistic situation assessment for abnormal interaction detection

T21 Multitarget tracking and sensor calibration in centralized and distributed networks

T22 Information fusion in resource-limited camera networks

T23 Introduction to Bayesian Filtering and Smoothing

T24 Sensor Fusion for Intelligent Vehicles
Retrieved from "https://fusion2016.org/index.php?title=Tutorials&oldid=324"
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