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<!-- CFP Download --> | <!-- CFP Download --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | ||
| 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> | | 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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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
<!-- List of Special Setutoialions of FUSION 2016 --> | <!-- List of Special Setutoialions of FUSION 2016 --> | ||
| − | | | + | | class="MainPageBG" style="width:100%; border:1px solid #fff784; background:#fffff7; vertical-align:top; color:#000;" | |
{| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;" | ||
| 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> | | 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#tutorial24| T24 Introduction to Bayesian Filtering and Smoothing]] | * [[Tutorials#tutorial24| T24 Introduction to Bayesian Filtering and Smoothing]] | ||
* [[Tutorials#tutorial25| T25 Sensor Fusion for Intelligent Vehicles]] | * [[Tutorials#tutorial25| T25 Sensor Fusion for Intelligent Vehicles]] | ||
| − | * [[Tutorials# | + | * [[Tutorials#tutorial26| T26 Multisensor Data Fusion in Shared Sensor and Actuator Networks]] |
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
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<!-- T1 Bayesian Multiple Target Tracking --> | <!-- T1 Bayesian Multiple Target Tracking --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;" | ||
| 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> | | 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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<!-- T2 Bayesian Networks and Trust Fusion with Subjective Logic --> | <!-- T2 Bayesian Networks and Trust Fusion with Subjective Logic --> | ||
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<!-- T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios --> | <!-- 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;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | ||
| 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> | | 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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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
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<!-- T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter --> | <!-- T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;" | ||
| 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> | | 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 --> | <!-- FUSION 2016 Tutorials --> | ||
{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
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<!-- T5 A Finite-Set Statistics Prime --> | <!-- T5 A Finite-Set Statistics Prime --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | ||
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T5 A Finite-Set Statistics Prime</h2> | | style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; 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 --> | <!-- FUSION 2016 Tutorials --> | ||
{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
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<!-- T6 Information Quality in Information Fusion and Decision Making --> | <!-- T6 Information Quality in Information Fusion and Decision Making --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;" | ||
| 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> | | 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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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
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<!-- T7 Multitarget Tracking and Multisensor Information Fusion --> | <!-- T7 Multitarget Tracking and Multisensor Information Fusion --> | ||
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<!-- T8 Overview of High-Level Information Fusion Theory, Models, and Representations --> | <!-- T8 Overview of High-Level Information Fusion Theory, Models, and Representations --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | ||
| 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> | | 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 --> | <!-- FUSION 2016 Tutorials --> | ||
{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
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<!-- T9 Quantum Physics Methods For Nonlinear Filtering --> | <!-- T9 Quantum Physics Methods For Nonlinear Filtering --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;" | ||
| 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> | | 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 --> | <!-- FUSION 2016 Tutorials --> | ||
{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | {| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;" | ||
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<!-- T10 Basic concepts in multiobject estimation --> | <!-- T10 Basic concepts in multiobject estimation --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | ||
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T10 Basic concepts in multiobject estimation</h2> | | style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; 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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<!-- T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion --> | <!-- T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;" | ||
| 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;">T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion</h2> | | 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;">T11 System-of-Systems Concepts, Opportunities and Itutoialues for Information Fusion</h2> | ||
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<!-- T12 Implementations of random-finite-set-based multi-target filters --> | <!-- T12 Implementations of random-finite-set-based multi-target filters --> | ||
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<!-- T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications --> | <!-- 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;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | ||
| 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;">T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications</h2> | | 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;">T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications</h2> | ||
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<!-- FUSION 2016 Tutorials --> | <!-- FUSION 2016 Tutorials --> | ||
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<!-- T14 Multistatic Exploration – Introduction to Modern Patutoialive Radar and Multistatic Tracking & Data Fusion --> | <!-- 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;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#fffff7;" | ||
| 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;">T14 Multistatic Exploration – Introduction to Modern Patutoialive Radar and Multistatic Tracking & Data Fusion</h2> | | 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;">T14 Multistatic Exploration – Introduction to Modern Patutoialive Radar and Multistatic Tracking & Data Fusion</h2> | ||
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<!-- FUSION 2016 Tutorials --> | <!-- FUSION 2016 Tutorials --> | ||
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<!-- T15 Big Data Fusion and Analytics --> | <!-- T15 Big Data Fusion and Analytics --> | ||
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | {| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;" | ||
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T15 Big Data Fusion and Analytics</h2> | | style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T15 Big Data Fusion and Analytics</h2> | ||
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<!-- T16 Object tracking, sensor fusion and situational awarenetutoial for atutoialisted- and self-driving vehicles: Problems, solutions and directions --> | <!-- T16 Object tracking, sensor fusion and situational awarenetutoial for atutoialisted- and self-driving vehicles: Problems, solutions and directions --> | ||
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