|
Twitter
|
Facebook
|
Google+
|
VKontakte
|
LinkedIn
|
Viadeo
|
English
|
Français
|
Español
|
العربية
|
 
International Journal of Innovation and Applied Studies
ISSN: 2028-9324     CODEN: IJIABO     OCLC Number: 828807274     ZDB-ID: 2703985-7
 
 
Friday 13 December 2024

About IJIAS

News

Submission

Downloads

Archives

Custom Search

Contact

  • Contact us
  • Newsletter:

Connect with IJIAS

  Now IJIAS is indexed in EBSCO, ResearchGate, ProQuest, Chemical Abstracts Service, Index Copernicus, IET Inspec Direct, Ulrichs Web, Google Scholar, CAS Abstracts, J-Gate, UDL Library, CiteSeerX, WorldCat, Scirus, Research Bible and getCited, etc.  
 
 
 

Smart Learning Tool for Kids with Real-Time Image Classification


Volume 44, Issue 1, November 2024, Pages 1–10

 Smart Learning Tool for Kids with Real-Time Image Classification

Moe Moe Zaw1 and Hla Hla Myint2

1 Faculty of Information and Communication Technology, University of Technology (Yatanarpon Cyber City), Myanmar
2 Department of Information Technology Supporting and Maintenance, University of Computer Studies (Magway), Magway, Myanmar

Original language: English

Copyright © 2024 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


The Smart Learning Tool for Kids with Real-time Image Classification is an AI-powered educational tool designed to assist young learners in recognizing and identifying objects through real-time image classification. The system captures images using a webcam, processes them through a Convolutional Neural Network (CNN) model and outputs the corresponding class label. It provides immediate audio feedback by pronouncing the class name in four languages: English, Myanmar, Thai and Chinese. The system aims to enhance kids’ learning experience by engaging multiple senses—visual and auditory—that makes learning interactive and multilingual. The CNN model is trained with custom training data, enabling accurate classification of 12 object classes. This system serves as a smart and user-friendly tool for early childhood education.

Author Keywords: Real-time Image Classification, Convolutional Neural Network (CNN), Multilingual Audio Feedback, Early Childhood Education, Interactive Learning, AI in Education.


How to Cite this Article


Moe Moe Zaw and Hla Hla Myint, “Smart Learning Tool for Kids with Real-Time Image Classification,” International Journal of Innovation and Applied Studies, vol. 44, no. 1, pp. 1–10, November 2024.