Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

The histological assessment of human tissue has emerged as the key challenge for
detection and treatment of cancer. A plethora of different data sources ranging from tissue …

Organizational decision-makers need to evaluate AI tools in light of increasing claims that
such tools outperform human experts. Yet, measuring the quality of knowledge work is …

Label noise is an important issue in classification, with many potential negative
consequences. For example, the accuracy of predictions may decrease, whereas the …

Abstract Many tasks in Natural Language Processing (NLP) and Computer Vision (CV) offer
evidence that humans disagree, from objective tasks such as part-of-speech tagging to more …

For many supervised learning tasks it may be infeasible (or very expensive) to obtain
objective and reliable labels. Instead, we can collect subjective (possibly noisy) labels from …

In a backdoor attack, an adversary injects corrupted data into a model's training dataset in
order to gain control over its predictions on images with a specific attacker-defined trigger. A …

Modern machine learning-based approaches to computer vision require very large
databases of labeled images. Some contemporary vision systems already require on the …

Distributing labeling tasks among hundreds or thousands of annotators is an increasingly
important method for annotating large datasets. We present a method for estimating the …

This paper addresses the repeated acquisition of labels for data items when the labeling is
imperfect. We examine the improvement (or lack thereof) in data quality via repeated …