Lloyd, Abad, Jhon and Michael, Barzo, Shan and Jan Aron, Fajardo, (2025) Machine Learning: School Uniform Detection System. International Journal of Innovative Science and Research Technology, 10 (5): 25may1106. pp. 858-879. ISSN 2456-2165
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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.
Item Type: | Article |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
Depositing User: | Editor IJISRT Publication |
Date Deposited: | 02 Jun 2025 11:32 |
Last Modified: | 02 Jun 2025 11:32 |
URI: | https://eprint.ijisrt.org/id/eprint/1038 |