Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …

In recent years, point cloud representation has become one of the research hotspots in the
field of computer vision, and has been widely used in many fields, such as autonomous …

Recent advances in deep neural networks (DNNs) have mainly focused on innovations in
network architecture and loss function. In this paper, we introduce a flexible high-order …

Continuously analyzing medical time series as new classes emerge is meaningful for health
monitoring and medical decision-making. Few-shot class-incremental learning (FSCIL) …

No system entity within a contemporary distributed cyber system can be entirely trusted.
Hence, the classic centralized trust management method cannot be directly applied to it …

The incremental learning paradigm in machine learning has consistently been a focus of
academic research. It is similar to the way in which biological systems learn, and reduces …

Given the prominence of 3D sensors in recent years, 3D point cloud scene data are worthy
to be further investigated. Point cloud scene understanding is a challenging task because of …

Person re-identification (Re-ID) has played an extremely crucial role in ensuring social
safety and has attracted considerable research attention. 3D shape information is an …

The self-attention (SA) network revisits the essence of data and has achieved remarkable
results in text processing and image analysis. SA is conceptualized as a set operator that is …

For robust person re-identification (Re-ID), the key is effectively learning the features of body
parts and their long-distance dependence. ResNet and Transformer are respectively good at …