Evaluating explanations of image classifiers regarding ground truth, eg segmentation masks
defined by human perception, primarily evaluates the quality of the models under …

How do neural network image classifiers respond to simpler and simpler inputs? And what
do such responses reveal about the learning process? To answer these questions, we need …

Convolutional Neural Networks (CNNs) have made significant progress on several
computer vision benchmarks, but are fraught with numerous non-human biases such as …

literature supporting the use of AI to complement radiologists' role in screening
mammography, with different models proposed in a double-reading environment. The …

The increasing complexity of artificial intelligence models has given rise to extensive work
toward understanding the inner workings of neural networks. Much of that work, however …

Rotator Cuff Tears (RCTs) are primarily age-related musculoskeletal disorders affecting the
shoulder region. In this paper, we present a research effort that aims to construct a Computer …

Artificial Intelligence (AI) research is broadly broken up into Narrow AI research and Artificial
General Intelligence (AGI). Narrow AI are AI that can complete specific tasks (such as image …

The goal of this study is to provide an objective criterion for computerised skin quality
assessment. Humans have been impacted by a variety of face features. Utilising eye …

Visual classification is the perceptible/computational effort of arranging objects and visual
contexts into distinct labels. Humans and machines have mastered this advanced problem …