The remote sensing (RS) field has an increasing research interest in using deep learning
(DL) models to recognize kinds of RS data, leading to a great demand for training data …

With the tremendous development of AI technologies, people will increasingly encounter
software algorithms that supervise their work. Algorithmic management is the term for AI that …

Crowdsourcing is a task‐solving model in which human crowd is hired to solve a particular
task. During the crowdsourcing process, the crowd selection is performed in order to select …

Crowdsourcing is a process of engaging a 'crowd'or a group of common people for
accomplishing the tasks. In this work, the time-bound tasks allocation problem in IoT-based …

This study introduces a laboratory experiment designed to assess the influence of
annotation strategies, levels of imbalanced data, and prior experience, on the performance …

Internet‐enabled technologies have provided a way for people to communicate and
collaborate with each other. The collaboration and communication made crowdsourcing an …

Crowdsourcing leverages the diverse skill sets of large collections of individual contributors
to solve problems and execute projects, where contributors may vary significantly in …

Crowdsourcing harnesses human effort to solve computer-hard problems. Such tasks often
have different levels of difficulty and workers have varying levels of skill at completing them …

A redundancy-based strategy is widely employed by assigning each task to multiple workers
and then inferring the correct answer (called truth) for each task in crowdsourcing. Most …

Worker reliability estimation is a fundamental problem in crowdsensing applications. This
paper proposes a robust feedback rating approach to estimate worker reliability explicitly. In …