AIMC Topic: Sign Language

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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition.

Scientific reports
Deaf and hard-of-hearing people utilize sign language recognition (SLR) to interconnect. Sign language (SL) is vital for hard-of-hearing and deaf individuals to communicate. SL uses varied hand gestures to speak words, sentences, or letters. It aids ...

SignFormer-GCN: Continuous sign language translation using spatio-temporal graph convolutional networks.

PloS one
Sign language is a complex visual language system that uses hand gestures, facial expressions, and body movements to convey meaning. It is the primary means of communication for millions of deaf and hard-of-hearing individuals worldwide. Tracking phy...

Triboelectric Bending Sensors for AI-Enabled Sign Language Recognition.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Human-machine interfaces and wearable electronics, as fundamentals to achieve human-machine interactions, are becoming increasingly essential in the era of the Internet of Things. However, contemporary wearable sensors based on resistive and capaciti...

Liquid-Metal-Based Multichannel Strain Sensor for Sign Language Gesture Classification Using Machine Learning.

ACS applied materials & interfaces
Liquid metals are highly conductive like metallic materials and have excellent deformability due to their liquid state, making them rather promising for flexible and stretchable wearable sensors. However, patterning liquid metals on soft substrates h...

STCNet: Spatio-Temporal Cross Network with subject-aware contrastive learning for hand gesture recognition in surface EMG.

Computers in biology and medicine
This paper introduces the Spatio-Temporal Cross Network (STCNet), a novel deep learning architecture tailored for robust hand gesture recognition in surface electromyography (sEMG) across multiple subjects. We address the challenges associated with t...

Machine Learning and Deep Learning Approaches for Arabic Sign Language Recognition: A Decade Systematic Literature Review.

Sensors (Basel, Switzerland)
Sign language (SL) is a means of communication that is used to bridge the gap between the deaf, hearing-impaired, and others. For Arabic speakers who are hard of hearing or deaf, Arabic Sign Language (ArSL) is a form of nonverbal communication. The d...

A Static Sign Language Recognition Method Enhanced with Self-Attention Mechanisms.

Sensors (Basel, Switzerland)
For the current wearable devices in the application of cross-diversified user groups, it is common to face the technical difficulties of static sign language recognition accuracy attenuation, weak anti-noise ability, and insufficient system robustnes...

Machine Learning-Assisted Gesture Sensor Made with Graphene/Carbon Nanotubes for Sign Language Recognition.

ACS applied materials & interfaces
Gesture sensors are essential to collect human movements for human-computer interfaces, but their application is normally hampered by the difficulties in achieving high sensitivity and an ultrawide response range simultaneously. In this article, insp...

Bengali-Sign: A Machine Learning-Based Bengali Sign Language Interpretation for Deaf and Non-Verbal People.

Sensors (Basel, Switzerland)
Sign language is undoubtedly a common way of communication among deaf and non-verbal people. But it is not common among hearing people to use sign language to express feelings or share information in everyday life. Therefore, a significant communicat...

Cross-modal knowledge distillation for continuous sign language recognition.

Neural networks : the official journal of the International Neural Network Society
Continuous Sign Language Recognition (CSLR) is a task which converts a sign language video into a gloss sequence. The existing deep learning based sign language recognition methods usually rely on large-scale training data and rich supervised informa...