Tutorial No.

Title

Presenters

T1

Registration and Fusion of Multiple Sensors for the 3D Reconstruction of the Environment with Classical and Deep Learning Methods

Nina Felicitas Heide

T2

Multitarget Tracking and Multisensor Information Fusion, FUSION 2020 Tutorial

Yaakov Bar-Shalom

T3

Introduction to Sensor Management

Kenneth Hintz

T4

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

Erik Blasch

T5

An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter

Felix Govaers

T6

Hyper-Heuristics and Data Fusion

Nelishia Pillay

T7

Deep Convolutional Neural Networked-based Multisensor Fusion for Computer Vision:Opportunities and Challenges

Fahimeh Farahnakian

T8

Practical use of Belief Function Theory: Tools and examples of applications

Sylvie Le Hegarat-Mascle

T9

Multisensor Data Fusion for Industry 4.0

Claudio de Farias and José Brancalion

T10

Evaluation of Technologies for Uncertainty Reasoning

Paulo Costa, Kathryn Laskey and Erik Blasch

T11

Estimation of Noise Parameters in State Space Models: Overview, Algorithms, and Comparison

Ondrej Straka and Jindrich Dunik

T12

Stone Soup: an open source tracking and state estimation framework; principles, use and applications

Jordi Barr

T13

Fusion using belief functions: source reliability and conflict

Frédéric Pichon and Anne-Laure Jousselme

T14

Poisson multi-Bernoulli mixtures for multiple target tracking

Angel Garcia-Fernandez, Yuxuan Xia, Karl Granstrom and Lennart Svensson

T15

Machine and Deep Learning for Data Fusion

Subrata Das

T16

Context-enhanced Information Fusion

Lauro Snidaro and Erik Blasch

T17

Tutorial on Robust Kalman Filtering

Florian Pfaff and Benjamin Noack

T18

Localization-of-Things: Foundations and Data Fusion

Moe Win and Andrea Conti

T19

Analytic Combinatorics for Multi-Object Tracking and Higher Level Fusion

Roy Streit and Murat Efe

T20

Multi Sensor Data Fusion for Vehicular Automation and Autonomous Driving: Concepts, Implementations and Evaluation Techniques

Bharanidhar Duraisamy, Ting Yuan, Tilo Schwarz, Martin Fritzsche and Michael Gabb

T21

Deep Feature Learning to Model Brain Network Activities

Narges Norouzi

 

TUTORIAL CO-CHAIRS

Denis Garagić, Stefano Coraluppi
email: tutorials@fusion2020.org