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 ...

Fig. 1. Overall Architecture. Our framework extracts spatial and dynamic features in parallel using the Slow and Fast pathways. Bi-directional Feature Fusion (BFF) facilitates the exchange of rich ...

This project was created as part of a final year major project with the goal of making communication more accessible. It uses real-time webcam input to detect and identify ASL gestures, converting ...

It has been reported that over 5 percent of the global population, approximately 430 million individuals, suffer from disabling hearing loss. In China, this number reaches approximately 30 million 1.

WARNER ROBINS, Ga. — Two Houston County High School students are making waves in the tech world with an app that translates American Sign Language (ASL) into English in real time. Michael Do and Hieu ...

In Colombia, approximately more than 500.000 people have disabling hearing loss, representing around 1% of the population in Colombia, and only 400 professional interpreters of Colombian Sign Language ...

Abstract: Hearing-impaired people cannot communicate with normal people easily. Most people are not aware of sign language recognition. To support this, machine learning and CV can be used to create ...

Abstract: Real-Time Sign Language Recognition (RTSLG) can help people express clearer thoughts, speak in shorter sentences, and be more expressive to use declarative language. Hand gestures provide a ...

Traditional facial recognition methods depend on a large number of training samples due to the massive turning of synaptic weights for low-level feature extractions. In prior work, a brain-inspired ...

Automated interpretation of echocardiography by deep neural networks could support clinical reporting and improve efficiency. Whereas previous studies have evaluated spatial relationships using still ...