# Human expert fusion for image classification

@article{Martin2008HumanEF, title={Human expert fusion for image classification}, author={Arnaud Martin and Christophe Osswald}, journal={ArXiv}, year={2008}, volume={abs/0806.1798} }

In image classification, merging the opinion of several huma n experts is very important for different tasks such as the evaluation or the t raining. Indeed, the ground truth is rarely known before the scene imaging. We propose here different models in order to fuse the informations given by two or more experts. The considered unit for the classification, a small tile of the im age, can contain one or more kind of the considered classes given by the experts. A second problem that we have to… Expand

#### 9 Citations

Fusion of heterogeneous remote sensing images by credibilist methods. (Fusion d'images de télédétection hétérogènes par méthodes crédibilistes)

- Computer Science
- 2017

This thesis focuses on the development of a new approach for the belief functions estimation based on Kohonen's map in order to simplify the masses assignment operation of the large volumes of data occupied by these images, and proposes an original fusion technique that will solve problems due to the wide variety of knowledge provided by these heterogeneous sensors. Expand

Fusion d'images par la théorie de Dezert-Smarandache (DSmT) en vue d'applications en télédétection

- Physics
- 2013

The main objective of this thesis is to provide automatic remote sensing tools of classi cation and of change detection of land cover for many purposes, in this context, we have developed two general… Expand

Generalized proportional conflict redistribution rule applied to Sonar imagery and Radar targets classification

- Computer Science
- ArXiv
- 2008

This chapter presents the advantages of the DSmT for the modelization of real applications and also for the combination step, and presents the formalization of the belief functionmodels, diﬀerent rules of combination and decision. Expand

Understanding the large family of Dempster-Shafer theory's fusion operators - a decision-based measure

- Computer Science
- 2006 9th International Conference on Information Fusion
- 2006

All the fusion operators tested with random belief functions are validated on the fusion of radar data classifiers, and show the interest of some new PCR methods. Expand

Toward Efficient Computation of the

- Mathematics
- 2013

Dempster-Shafer (DS) belief theory provides a con- venient framework for the development of powerful data fusion engines by allowing for a convenient representation of a wide variety of data… Expand

Evidence combination for a large number of sources

- Computer Science
- 2017 20th International Conference on Information Fusion (Fusion)
- 2017

A combination rule for a large number of sources, named LNS (stands for Large Number of Sources), is proposed on the basis of a simple idea: the more common ideas one source shares with others, the more reliable the source is. Expand

Conflict management in information fusion with belief functions

- Computer Science
- Information Quality in Information Fusion and Decision Making
- 2019

This chapter proposes a discussion to consider the conflict in information fusion with the theory of belief functions and some approaches have been proposed in order to manage this conflict or to decide with conflicting mass functions. Expand

Belief Detection and Temporal Analysis of Experts in Question Answering Communities: case study Stack Overflow. (Détection et Analyse Temporelle des Experts dans les Réseaux Communautaires de Questions Réponses : étude de cas Stack Overflow)

- Computer Science
- 2017

A general measure of expertise based on the theory of belief functions is proposed, which will allow us to classify users and detect the most knowledgeable persons, and how do users evolve during their time spent within the platform is described. Expand

Influencers characterization in a social network for viral marketing perspectives. (Caractérisation des influenceurs dans un réseau social pour des perspectives de Marketing viral)

- Computer Science
- 2016

This thesis proposes two evidential influence maximization models for social networks that uses the theory of belief functions to estimate users influence and introduces an influence measure that fuses many influence aspects, like the importance of the user in the network and the popularity of his messages. Expand

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