Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …

Face recognition is one of the most active research fields of computer vision and pattern
recognition, with many practical and commercial applications including identification, access …

Detecting out-of-distribution inputs is critical for the safe deployment of machine learning
models in the real world. However, neural networks are known to suffer from the …

The performance of face recognition system degrades when the variability of the acquired
faces increases. Prior work alleviates this issue by either monitoring the face quality in pre …

Heterogeneous graph neural networks (HGNNs) have been blossoming in recent years, but
the unique data processing and evaluation setups used by each work obstruct a full …

This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming
to maximize the within-class similarity s_p and minimize the between-class similarity s_n …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

Contemporary domain adaptation methods are very effective at aligning feature distributions
of source and target domains without any target supervision. However, we show that these …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

Gait recognition is an appealing biometric modality which aims to identify individuals based
on the way they walk. Deep learning has reshaped the research landscape in this area …