The high dimension, complexity, and imbalance of network data are hot issues in the field of
intrusion detection. Nowadays, intrusion detection systems face some challenges in …

Video analysis tasks such as action recognition have received increasing research interest
with growing applications in fields such as smart healthcare, thanks to the introduction of …

Abstract 3D human motion prediction, predicting future poses from a given sequence, is an
issue of great significance and challenge in computer vision and machine intelligence …

Video Visual Relation Detection (VidVRD) aims to semantically describe the dynamic
interactions across visual concepts localized in a video in the form of subject, predicate …

Automatically generating the “impression” section of a radiology report given the “findings”
section can summarize as much salient information of the “findings” section as possible, thus …

Few-shot video action recognition is an effective approach to recognizing new categories
with only a few labeled examples, thereby reducing the challenges associated with …

Temporal action localization is currently an active research topic in computer vision and
machine learning due to its usage in smart surveillance. It is a challenging problem since the …

Few-shot action recognition aims to address the high cost and impracticality of manually
labeling complex and variable video data in action recognition. It requires accurately …

Numeral recognition plays a crucial role in creating automated systems such as posting
address sorting and license plate recognition. Nowadays, numeral recognition systems …

In skeleton-based action recognition, graph convolutional networks (GCNs), which model
human body skeletons using graphical components such as nodes and connections, have …