[HTML][HTML] A survey on sign language literature
M Alaghband, HR Maghroor, I Garibay - Machine Learning with …, 2023 - Elsevier
Individuals with hearing impairment encounter various types and levels of difficulties,
highlighting the need for more research to provide effective support. One significant difficulty …
highlighting the need for more research to provide effective support. One significant difficulty …
[HTML][HTML] Multistage spatial attention-based neural network for hand gesture recognition
The definition of human-computer interaction (HCI) has changed in the current year because
people are interested in their various ergonomic devices ways. Many researchers have …
people are interested in their various ergonomic devices ways. Many researchers have …
[HTML][HTML] Deep learning for highly accurate hand recognition based on yolov7 model
Hand detection is a key step in the pre-processing stage of many computer vision tasks
because human hands are involved in the activity. Some examples of such tasks are hand …
because human hands are involved in the activity. Some examples of such tasks are hand …
Isolated arabic sign language recognition using a transformer-based model and landmark keypoints
Pose-based approaches for sign language recognition provide light-weight and fast models
that can be adopted in real-time applications. This article presents a framework for isolated …
that can be adopted in real-time applications. This article presents a framework for isolated …
[HTML][HTML] American sign language words recognition of skeletal videos using processed video driven multi-stacked deep LSTM
SB Abdullahi, K Chamnongthai - Sensors, 2022 - mdpi.com
Complex hand gesture interactions among dynamic sign words may lead to
misclassification, which affects the recognition accuracy of the ubiquitous sign language …
misclassification, which affects the recognition accuracy of the ubiquitous sign language …
[HTML][HTML] Multi-stream general and graph-based deep neural networks for skeleton-based sign language recognition
Sign language recognition (SLR) aims to bridge speech-impaired and general communities
by recognizing signs from given videos. However, due to the complex background, light …
by recognizing signs from given videos. However, due to the complex background, light …
Intelligent sign language recognition system for e-learning context
MJ Hussain, A Shaoor, SA Alsuhibany, YY Ghadi… - 2022 - digitallibrary.aau.ac.ae
In this research work, an efficient sign language recognition tool for e-learning has been
proposed with a new type of feature set based on angle and lines. This feature set has the …
proposed with a new type of feature set based on angle and lines. This feature set has the …
Sign language recognition using graph and general deep neural network based on large scale dataset
Sign Language Recognition (SLR) represents a revolutionary technology aiming to
establish communication between hearing impaired and non-hearing impaired …
establish communication between hearing impaired and non-hearing impaired …
Hand gesture recognition for characters understanding using convex Hull landmarks and geometric features
With the latest advancements, hand gesture recognition is becoming an effective way of
communication and gaining popularity from a research point of view. Hearing impaired …
communication and gaining popularity from a research point of view. Hearing impaired …
[HTML][HTML] Recursive feature elimination for improving learning points on hand-sign recognition
Hand gestures and poses allow us to perform non-verbal communication. Sign language is
becoming more important with the increase in the number of deaf and hard-of-hearing …
becoming more important with the increase in the number of deaf and hard-of-hearing …