A comparison of convolutional neural networks for Kazakh sign language recognition
For people with disabilities, sign language is the most important means of communication. Therefore, more and more authors of various papers and scientists around the world are proposing solutions to use intelligent hand gesture recognition systems. Such a system is aimed not only for those who wish...
Saved in:
Main Authors: | Chingiz Kenshimov, Samat Mukhanov, Timur Merembayev, Didar Yedilkhan |
---|---|
Format: | article |
Language: | EN RU UK |
Published: |
PC Technology Center
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/bbffd941b98c492e9d9606919a0e9b09 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Review of the Hand Gesture Recognition System: Current Progress and Future Directions
by: Noraini Mohamed, et al.
Published: (2021) -
Improvement of the model of object recognition in aero photographs using deep convolutional neural networks
by: Vadym Slyusar, et al.
Published: (2021) -
Egocentric Gesture Recognition Using 3D Convolutional Neural Networks for the Spatiotemporal Adaptation of Collaborative Robots
by: Dimitris Papanagiotou, et al.
Published: (2021) -
A Novel EMG-Based Hand Gesture Recognition Framework Based on Multivariate Variational Mode Decomposition
by: Kun Yang, et al.
Published: (2021) -
Analysis of fault diagnosis of DC motors by power consumption pattern recognition
by: Hasan Shakir Majdi, et al.
Published: (2021)