Year: 2025
Type: article
Abstract: The rapid increasing demand in advent of technology needing to adopt to real-world instances, had led to the development of AI solutions for SEAIT in response for school uniform compliance. This study employs Machine Learning – School Uniform Detection System utilizing Incremental Process Model, an Agile Methodology that ensures systematic and adaptive presentation to system development. The system utilizes Machine Learning techniques, particularly camera vision, to accurately detect and fragment and confirm students’ uniforms in real time. By increasingly innovating and refining the model, the development process enhances system acceptability and accuracy while answering challenges such as variations in lighting, posture, and uniform designs. The study involves image pigmentations, feature extraction, and deep learning algorithms, allowing efficient uniform detection with less human intervention. The system assists school admin in enforcing school policies, reducing manual workload. Future innovations may include integrating facial recognition for customized monitoring and improving model with a more extensive dataset. Thus, this study must be implemented.
Authors: Abad, Jhon Lloyd, Barzo, Shan Michael, Fajardo, Jan Aron, Reginald S. Prudente, Joseph M. Buquis, Kenmark T. Celis
Institution: South East Asian Institute of Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4410588121