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ORCIDBELIEF 2016: Prague, Czech Republic
- Jirina Vejnarová, Václav Kratochvíl:
Belief Functions: Theory and Applications - 4th International Conference, BELIEF 2016, Prague, Czech Republic, September 21-23, 2016, Proceedings. Lecture Notes in Computer Science 9861, Springer 2016, ISBN 978-3-319-45558-7
Theoretical Issues
- Radim Jirousek, Prakash P. Shenoy
:
Entropy of Belief Functions in the Dempster-Shafer Theory: A New Perspective. 3-13 - Liping Liu:
A New Matrix Addition Rule for Combining Linear Belief Functions. 14-24 - Alexander Lepskiy:
On Internal Conflict as an External Conflict of a Decomposition of Evidence. 25-34
Decission
- David Burke:
Designing an Evidential Assertion Language for Multiple Analysts. 37-45 - Simon Carladous, Jean-Marc Tacnet, Jean Dezert, Guillaume Dupouy, Mireille Batton-Hubert:
A New ER-MCDA Mapping for Decision-Making Based on Imperfect Information. 46-55 - Simon Carladous, Jean-Marc Tacnet, Jean Dezert, Deqiang Han, Mireille Batton-Hubert:
Applying ER-MCDA and BF-TOPSIS to Decide on Effectiveness of Torrent Protection. 56-65 - Jean Dezert, Deqiang Han, Jean-Marc Tacnet, Simon Carladous, Yi Yang:
Decision-Making with Belief Interval Distance. 66-74 - Jean Dezert, Deqiang Han, Jean-Marc Tacnet, Simon Carladous, Hanlin Yin:
The BF-TOPSIS Approach for Solving Non-classical MCDM Problems. 75-83 - Nopadon Kronprasert, Nattika Thipnee:
Use of Evidence Theory in Fault Tree Analysis for Road Safety Inspection. 84-93
Classification
- Amal Ben Rjab, Mouloud Kharoune, Zoltán Miklós, Arnaud Martin:
Characterization of Experts in Crowdsourcing Platforms. 97-104 - Orakanya Kanjanatarakul, Songsak Sriboonchitta, Thierry Denoeux:
k-EVCLUS: Clustering Large Dissimilarity Data in the Belief Function Framework. 105-112 - Marie Lachaize, Sylvie Le Hégarat-Mascle, Emanuel Aldea, Aude Maitrot, Roger Reynaud:
SVM Classifier Fusion Using Belief Functions: Application to Hyperspectral Data Classification. 113-122 - Kuang Zhou, Arnaud Martin, Quan Pan:
Semi-supervised Evidential Label Propagation Algorithm for Graph Data. 123-133
Information Fusion
- Andrey G. Bronevich, Igor N. Rozenberg:
Conjunctive Rules in the Theory of Belief Functions and Their Justification Through Decisions Models. 137-145 - Milan Daniel:
A Relationship of Conflicting Belief Masses to Open World Assumption. 146-155 - John Klein, Sébastien Destercke, Olivier Colot:
Idempotent Conjunctive Combination of Belief Functions by Distance Minimization. 156-163 - Václav Kratochvíl, Jirina Vejnarová:
IPFP and Further Experiments. 164-173 - Johan Schubert:
Entropy-Based Counter-Deception in Information Fusion. 174-181 - Liqi Sui, Pierre Feissel, Thierry Denoeux:
Identification of Elastic Properties Based on Belief Function Inference. 182-189 - Rui Wang, Jérémie Guiochet, Gilles Motet, Walter Schön:
D-S Theory for Argument Confidence Assessment. 190-200
Applications
- Lin An, Ming Li, Mohamed El Yazid Boudaren, Wojciech Pieczynski:
Evidential Correlated Gaussian Mixture Markov Model for Pixel Labeling Problem. 203-211 - Nathalie Helal, Frédéric Pichon, Daniel Porumbel, David Mercier, Eric Lefèvre:
The Capacitated Vehicle Routing Problem with Evidential Demands: A Belief-Constrained Programming Approach. 212-221 - Pauline Minary, Frédéric Pichon, David Mercier, Eric Lefèvre, Benjamin Droit:
An Evidential Pixel-Based Face Blurring Approach. 222-230 - Thanuka L. Wickramarathne:
Integrity Preserving Belief Update for Recursive Bayesian Tracking with Non-ideal Sensors. 231-240 - Salim Zair, Sylvie Le Hégarat-Mascle, Emmanuel Seignez:
An Evidential RANSAC Algorithm and Its Application to GNSS Positioning. 241-250
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