Skip To Main Content
Pathomthat Chiradeja on Muck Rack

Pathomthat Chiradeja

As seen in: MDPI
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Pathomthat

Contact Pathomthat, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Sign Language Sentence Recognition Using Hybrid Graph Embedding and Adaptive Convolutional Networks

|
By Pathomthat Chiradeja, Yijuan Liang, Chaiyan Jettanasen
| MDPI
1. Background and Significance Despite technological advances, deaf and hard-of-hearing people face difficulties with language [1]. Deaf people worldwide face important communication gaps because traditional communication tools struggle to understand sign language’s multidimensionality [2]. Computer-sensor-based machine learning and assistive technology are used in sign language recognition (SLR).
Open in Who Shared Issue with article?

Exploration of Sign Language Recognition Methods Based on Improved YOLOv5s

|
By Xiaohua Li, Chaiyan Jettanasen, Pathomthat Chiradeja
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Open in Who Shared View Duplicates (137) Issue with article?

Progression Learning Convolution Neural Model-Based Sign Language Recognition Using Wearable Glove Devices

|
By Chaiyan Jettanasen, Pathomthat Chiradeja, Yijuan Liang
| MDPI
1. Introduction Sign language, a structured sequence of hand motions, provides the most efficient means of communication for deaf people. Hard-of-hearing people have traditionally used sign language to interact with each other. The available approaches to the interpretation of sign language utilize vision techniques to translate signs autonomously. This primarily entails two tasks: isolated or word-based recognition and continuous or sentence-based recognition.
Open in Who Shared Issue with article?
See all 6 articles