Image tagging is an essential step for developing Automatic Image Annotation (AIA)
methods that are based on the learning by example paradigm. However, manual image …

Abstract Analysis of emotions elicited by opinions, comments, or articles commonly exploits
annotated corpora, in which the labels assigned to documents average the views of all …

This paper presents a classification framework and a systematic analysis of literature on
answer aggregation techniques for the most popular and important type of crowdsourcing …

Crowdsourcing is an economic and efficient strategy aimed at collecting annotations of data
through an online platform. Crowd workers with different expertise are paid for their service …

Although it has become an accepted lay view that when labeling objects through
crowdsourcing systems, non-expert annotators often exhibit biases, this argument lacks …

The swift development of the multimedia technology has raised dramatically the users'
expectation on the quality of experience. To obtain the ground-truth perceptual quality for …

Image tagging is an essential step for developing automatic image annotation methods that
are based on the learning by example paradigm. However, manual image annotation, even …

Several approaches have been proposed to estimate quality in subjective experiments while
highlighting peculiar subject behaviors. However, there is some room for improvement in …

Over the last decade, a plethora of training datasets have been compiled for use in
language-based machine perception and in human-centered AI, alongside research …

Multiple-criteria decision-making (MCDM) typically assumes that crowds make completely
rational decisions. In MCDM, a crowd as a whole, or its individual members, generally make …