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<!-- T1 Bayesian Multiple Target Tracking --> | <!-- T1 Bayesian Multiple Target Tracking --> | ||
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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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<!-- 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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<!-- T5 An Introduction to Finite-Set Statistics for Information Fusion --> | <!-- T5 An Introduction to Finite-Set Statistics for Information Fusion --> | ||
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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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<!-- T9 Quantum Physics Methods for Nonlinear Filtering --> | <!-- T9 Quantum Physics Methods for Nonlinear Filtering --> | ||
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<!-- T10 Basic Concepts in Multiobject Estimation --> | <!-- T10 Basic Concepts in Multiobject Estimation --> | ||
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<!-- T11 System-of-Systems Concepts, Opportunities and Issues for Information Fusion --> | <!-- T11 System-of-Systems Concepts, Opportunities and Issues for Information Fusion --> | ||
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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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<!-- T14 Multistatic Exploration – Introduction to Modern Passive Radar and Multistatic Tracking & Data Fusion --> | <!-- T14 Multistatic Exploration – Introduction to Modern Passive Radar and Multistatic Tracking & Data Fusion --> | ||
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<!-- T15 Big Data Fusion and Analytics --> | <!-- T15 Big Data Fusion and Analytics --> | ||
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<!-- T16 Object Tracking, Sensor Fusion and Situational Awareness for Assisted- and Self-Driving Vehicles: Problems, Solutions and Directions --> | <!-- T16 Object Tracking, Sensor Fusion and Situational Awareness for Assisted- and Self-Driving Vehicles: Problems, Solutions and Directions --> | ||
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<!-- T17 Emerging Quantum Technologies for Fusion --> | <!-- T17 Emerging Quantum Technologies for Fusion --> | ||
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<!-- T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods --> | <!-- T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods --> | ||
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<!-- T19 Integration of Information to Identify Objects in Big Data --> | <!-- T19 Integration of Information to Identify Objects in Big Data --> | ||
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<!-- T20 Extended Object Tracking: Theory and Applications --> | <!-- T20 Extended Object Tracking: Theory and Applications --> | ||
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<!-- T21 Probabilistic Situation Assessment for Abnormal Interaction Detection --> | <!-- T21 Probabilistic Situation Assessment for Abnormal Interaction Detection --> | ||
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<!-- T22 Multitarget Tracking and Sensor Calibration in Centralized and Distributed Networks --> | <!-- T22 Multitarget Tracking and Sensor Calibration in Centralized and Distributed Networks --> | ||
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<!-- T23 Information Fusion in Resource-Limited Camera Networks --> | <!-- T23 Information Fusion in Resource-Limited Camera Networks --> | ||
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<!-- T24 Introduction to Bayesian Filtering and Smoothing --> | <!-- T24 Introduction to Bayesian Filtering and Smoothing --> | ||
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<!-- T25 Sensor Fusion for Intelligent Vehicles --> | <!-- T25 Sensor Fusion for Intelligent Vehicles --> | ||
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Revision as of 09:50, 1 April 2016
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