# Application of Facial Expression Using YOLOv11 to Measure Interest in Training Materials
> Imran I.

URL kanonis: https://discover.unhas.ac.id/publications/application-of-facial-expression-using-yolov11-to-measure-interest-in-training-m
Jurnal / Konferensi: International Journal of Basic and Applied Sciences
Tahun terbit: 2025
DOI: https://doi.org/10.14419/vxgf1w29
ISSN: 22275053
Citations: 0

## Authors
- Imran I.

## Abstract
The purpose of this study is to assess trainees' proficiency with the Convolutional Neural ‎Network (CNN) model in recognizing emotions from facial expressions. A wide range of ‎applications in training, education, and human-machine interaction could benefit greatly from ‎computer vision-based emotion recognition. A CNN model created especially to identify ‎important emotions including happiness, sadness, anger, and fear is trained and tested in this ‎study using a dataset of facial expressions. The test findings demonstrate that the CNN model ‎can accurately and efficiently classify emotions and offer valuable information about trainees' ‎strengths and limitations in identifying different emotions. This study emphasizes how CNN-‎based technology may be used to help assess and enhance emotion recognition skills in the ‎setting of professional training‎.

## Keywords
- Measure (data warehouse)
- Facial expression
- Training (meteorology)
- Computer science
- Expression (computer science)
- Artificial intelligence
- Data mining
- Geography
- Programming language
- Meteorology

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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