Abstract Facial Action Units (AU) is a vital concept in the realm of affective computing, and
AU detection has always been a hot research topic. Existing methods suffer from overfitting …

Facial affective behavior analysis (FABA) is crucial for understanding human mental states
from images. However, traditional approaches primarily deploy models to discriminate …

Facial Action Unit (AU) detection has gained significant research attention as AUs contain
complex expression information. In this paper, we unpack two fundamental factors in AU …

The increasing integration of machine learning algorithms in daily life underscores the
critical need for fairness and equity in their deployment. As these technologies play a pivotal …

Facial expression recognition (FER) is a critical task in multimedia with significant
implications across various domains. However, analyzing the causes of facial expressions is …

Evaluating affect analysis methods presents challenges due to inconsistencies in database
partitioning and evaluation protocols, leading to unfair and biased results. Previous studies …

Background The latest international multidisciplinary histopathological classification of lung
cancer indicates that a deeper study of the lung adenocarcinoma requires a comprehensive …

The long-standing problem of geometric problem solving in artificial intelligence education
has attracted widespread attention. It is necessary to combine geometry diagrams and text …

For the Facial Action Unit (AU) detection task, accurately capturing the subtle facial
differences between distinct AUs is essential for reliable detection. Additionally, AU …

Representation learning is a machine learning technique aimed at automatically discovering
the most informative features of raw data, transforming it into a representation that captures …