The accuracy of a classification is fundamental to its interpretation, use and ultimately
decision making. Unfortunately, the apparent accuracy assessed can differ greatly from the …

Abstract Domain generalization-based fault diagnosis (DGFD) has garnered significant
attention due to its ability to generalize prior diagnostic knowledge to unseen working …

The long-tailed data distribution is prevalent in real world and it poses great challenge on
deep neural network training. In this paper, we propose Margin-aware Rectified …

Early detection of melanoma remains a daily challenge due to the increasing number of
cases and the lack of dermatologists. Thus, AI-assisted diagnosis is considered as a …

As the most common idiopathic inflammatory myopathy in children, juvenile dermatomyositis
(JDM) is characterized by skin rashes and muscle weakness. The childhood myositis …

Weather forecasting has been playing an important role in socio-economics. However,
operational numerical weather prediction (NWP) is insufficiently accurate in terms of …

It is usually supposed that training database is manually balanced in traditional visual
recognition tasks. However, in nature, data tends to follow long-tailed distributions. In recent …

In the field of computational physics and material science, the efficient sampling of rare
events occurring at atomic scale is crucial. It aids in understanding mechanisms behind a …

Dealing with significant class imbalance poses a significant challenge in various real-world
applications, particularly when the accurate classification and generalization of minority …

When the training dataset follows a long-tail distribution, models tend to prioritize the
majority of the data, thus resulting in lower predictive accuracy for the minority data. Among …