Abstract: We consider the problem of detecting and localizing a human ... latency in detection of actions. In this paper, we introduce a greedy approach to detect the action class, invariant of their ...

The work is published in the journal Nature Communications ... Natural language processing models reveal neural dynamics of human conversation, Nature Communications (2025).

With extracted information as input, we model human action anomaly detection in operations using both spatial and temporal dimensions. We validated our work with the composed network on our own ...

“These results provide initial validation of the broader potential use of NUZ-001 in other neurodegenerative diseases, highlighting its safety and efficacy in ArtiBrain™ 3D human micro-tissues model.

A Human Action Recognition (HAR) model combining 3D CNN and LSTM networks to accurately recognize actions in videos using spatial-temporal feature extraction. Trained on UCF-50 and outperforming ...

Department of Pediatric Surgery, Sophia Children’s Hospital, Erasmus Medical Center, Rotterdam 3000 CB, The Netherlands Department of Cell Biology, Erasmus Medical Center, Rotterdam 3000 CB, The ...

Researchers develop an AI-driven video analyzer capable of detecting human ... the work published in the article "A Semantic and Motion-Aware Spatiotemporal Transformer Network for Action ...

“This AI technology opens doors for real-time action detection in ... and understand complex human behaviors. The first is a multi-feature selective attention model, which helps the AI focus ...

So, how does it work? At its core, SMAST is powered by artificial intelligence. The system relies on two key components to detect and understand complex human behaviors. The first is a multi-feature ...