Acknowledgement
본 연구는 과학기술정보통신부 및 정보통신기획평가원의 SW중심대학사업의 연구결과로 수행되었음 (2018-0-00209)
Proceedings of the Korean Society of Computer Information Conference (한국컴퓨터정보학회:학술대회논문집)
- 2023.07a
- /
- Pages.45-46
- /
- 2023
YOLOv5 in ESL: Object Detection for Engaging Learning
ESL의 YOLOv5: 참여 학습을 위한 객체 감지
- John Edward Padilla (Dept. of Digital Media, Soongsil University) ;
- Kang-Hee Lee (Dept. of Digital Media, Soongsil University)
- Published : 2023.07.12
Abstract
In order to improve and promote immersive learning experiences for English as a Second Language (ESL) students, the deployment of a YOLOv5 model for object identification in videos is proposed. The procedure includes collecting annotated datasets, preparing the data, and then fine-tuning a model using the YOLOv5 framework. The study's major objective is to integrate a well-trained model into ESL instruction in order to analyze the effectiveness of AI application in the field.