Deep learning from crowds

Understand

Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the state-of-the-art in various domains.

• However, as the size of supervised artificial neural networks grows, typically so does the need for larger labeled datasets.
• Recently, crowdsourcing has established itself as an efficient and cost-effective solution for labeling large sets of data in a scalable manner, but it often requires aggregating labels from multiple noisy contributors with different levels of expertise.
• In this paper, we address the problem of learning deep neural networks from crowds.