Purpose Over the past decade, many research works in various disciplines have benefited
from the endless ocean of people and their potentials (in the form of crowdsourcing) as an …

Evaluating the effectiveness of defense technologies mandates the inclusion of a human
element, specifically if these technologies target human cognition and emotions. One of the …

Crowdsourcing is a popular methodology to collect manual labels at scale. Such labels are
often used to train AI models and, thus, quality control is a key aspect in the process. One of …

Crowdsourcing is an information system that provides a cost-effective way of solving
computationally challenging problems. However, it is potentially vulnerable to adversarial …

Despite its successes in various machine learning and data science tasks, crowdsourcing
can be susceptible to attacks from dedicated adversaries. This work investigates the effects …

As an effective way to solicit useful information from the crowd, crowdsourcing has emerged
as a popular paradigm to solve challenging tasks. However, the data provided by the …

Learning from Crowds (LFC) seeks to induce a high-quality classifier from training instances,
which are linked to a range of possible noisy annotations from crowdsourcing workers under …

Crowdsourcing have been gaining increasing popularity as a highly distributed digital
solution that surpasses both borders and time-zones. Moreover, it extends economic …

Crowdsourcing is an emerging paradigm in AI and machine learning. It involves gathering
input from human crowds, usually through the Internet, to solve a given task. Due to its open …

Crowdsourcing has achieved great success in fields like data annotation, social survey,
objects labeling, etc. However, enticed by potential high rewards, we have seen more and …