GESTURE RECOGNITION OF MACHINE LEARNING AND CONVOLUTIONAL NEURAL NETWORK METHODS FOR KAZAKH SIGN LANGUAGE
Journal Title: Scientific Journal of Astana IT University - Year 2023, Vol 15, Issue 15
Abstract
Recently, there has been a growing interest in machine learning and neural networks among the public, largely due to advancements in technology which have led to improved methods of computer recognition of objects, sounds, texts, and other data types. As a result, human-computer interactions are becoming more natural and comprehensible to the average person. The progress in computer vision has enabled the use of increasingly sophisticated models for object recognition in images and videos, which can also be applied to recognize hand gestures. In this research, popular hand gesture recognition models, such as the Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Support Vector Machine (SVM) were examined. These models vary in their approaches, processing time, and training data size. The important feature of this research work is the use of various machine learning algorithms and methods such as CNN, LSTM, and SVM. Experiments showed different results when training neural networks for sign language recognition in the Kazakh sign language based on the dactyl alphabet. This article provides a detailed description of each method, their respective purposes, and effectiveness in terms of performance and training. Numerous experimental results were recorded in a table, demonstrating the accuracy of recognizing each gesture. Additionally, specific hand gestures were isolated for testing in front of the camera to recognize the gesture and display the result on the screen. An important feature was the use of mathematical formulas and functions to explain the working principle of the machine learning algorithm, as well as the logical scheme and structure of the LSTM algorithm.
Authors and Affiliations
Samat Mukhanov, Raissa Uskenbayeva , Young Im Cho, Dauren Kabyl, Nurzhan Les, Maqsat Amangeldi
Keywords
Related Articles
- EP ID EP723061
- DOI -
- Views 78
- Downloads 0
THE EMOTIONAL INFECTION OF THE VIRTUAL INNOVATION PROJECT TEAM
Emotional infection is considered as a social and psychological mechanism of transferring the mental mood of the manager to the virtual project team and stakeholders of the projects. Emotional impact in the face of dir...
DEVELOPMENT OF A QUESTION ANSWERING CHATBOT FOR BLOCKCHAIN DOMAIN
Large Language Models (LLMs), such as ChatGPT, have transformed the field of natural language processing with their capacity for language comprehension and generation of human-like, fluent responses for many downstream t...
PROTEIN IDENTIFICATION USING SEQUENCE DATABASES
The bottom-up proteomics approach (also known as the shotgun approach), based on the digestion of proteins in peptides and their sequencing using tandem mass spectrometry (MS/MS), has become widespread. The identificat...
DISTRIBUTION OF ETHEREUM BLOCKCHAIN ADDRESSES
In the contemporary world, Ethereum is a very reliable financial saving among cryptocurrencies. It is also well known as a blockchain platform for creating and launching its own cryptocurrency. The applications run on...
A CONCEPTUAL MODEL AND PROCESS MANAGEMENT METHOD OF THE PLANNING AND MONITORING OF THE WORKLOAD IN THE EDUCATIONAL ENVIRONMENT
The article formulates the aims of HEI’s activities, as well as approaches to managing all actions that ensure the achievement of the stated aims. The process approach is defined as the main one in the university managem...