[HTML][HTML] Machine learning methods for sign language recognition: A critical review and analysis
Sign language is an essential tool to bridge the communication gap between normal and
hearing-impaired people. However, the diversity of over 7000 present-day sign languages …
hearing-impaired people. However, the diversity of over 7000 present-day sign languages …
Artificial intelligence technologies for sign language
I Papastratis, C Chatzikonstantinou, D Konstantinidis… - Sensors, 2021 - mdpi.com
AI technologies can play an important role in breaking down the communication barriers of
deaf or hearing-impaired people with other communities, contributing significantly to their …
deaf or hearing-impaired people with other communities, contributing significantly to their …
Deepsign: Sign language detection and recognition using deep learning
The predominant means of communication is speech; however, there are persons whose
speaking or hearing abilities are impaired. Communication presents a significant barrier for …
speaking or hearing abilities are impaired. Communication presents a significant barrier for …
An integrated mediapipe-optimized GRU model for Indian sign language recognition
Sign language recognition is challenged by problems, such as accurate tracking of hand
gestures, occlusion of hands, and high computational cost. Recently, it has benefited from …
gestures, occlusion of hands, and high computational cost. Recently, it has benefited from …
Quantitative survey of the state of the art in sign language recognition
O Koller - arXiv preprint arXiv:2008.09918, 2020 - arxiv.org
This work presents a meta study covering around 300 published sign language recognition
papers with over 400 experimental results. It includes most papers between the start of the …
papers with over 400 experimental results. It includes most papers between the start of the …
Deep BLSTM-GRU model for monthly rainfall prediction: A case study of Simtokha, Bhutan
Rainfall prediction is an important task due to the dependence of many people on it,
especially in the agriculture sector. Prediction is difficult and even more complex due to the …
especially in the agriculture sector. Prediction is difficult and even more complex due to the …
DeepArSLR: A novel signer-independent deep learning framework for isolated arabic sign language gestures recognition
Hand gesture recognition has attracted the attention of many researchers due to its wide
applications in robotics, games, virtual reality, sign language and human-computer …
applications in robotics, games, virtual reality, sign language and human-computer …
Advances in machine translation for sign language: approaches, limitations, and challenges
Sign languages are used by the deaf community around the globe to communicate with one
another. These are gesture-based languages where a deaf person performs gestures using …
another. These are gesture-based languages where a deaf person performs gestures using …
A comprehensive survey and taxonomy of sign language research
ESM El-Alfy, H Luqman - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
Sign language relies on visual gestures of human body parts to convey meaning and plays
a vital role in modern society to communicate and interact with people having hearing …
a vital role in modern society to communicate and interact with people having hearing …
A novel hybrid bidirectional unidirectional LSTM network for dynamic hand gesture recognition with leap motion
Due to the recent development of machine learning and sensor innovations, hand gesture
recognition systems become promising for the digital entertainment field. In this paper, we …
recognition systems become promising for the digital entertainment field. In this paper, we …