Abstract: Vision-based human activity recognition (HAR) techniques have garnered significant attention and extensive research, with successful applications in many scenarios. However, their ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

Agents use facial recognition, social media monitoring and other tech tools not only to identify undocumented immigrants but also to track protesters, current and former officials said. By Sheera ...

This paper proposes a multi-modal deep learning framework for Arabic Sign Language (ArSL) recognition, addressing the challenges of both static and dynamic gesture recognition. The framework ...

In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. Zahra Ghorrati is developing frameworks for human activity ...

Accurate gait-phase identification in children with Cerebral Palsy (CP) constitutes a pivotal prerequisite for evidence-based rehabilitation. Addressing the precise detection of gait disturbances ...

Abstract: The increasing elderly population necessitates intelligent monitoring systems to ensure safety, independence and well-being. This study introduces a deep learning-based real-time video-based ...