<![CDATA[Machine learning is a branch of artificial intelligence that enables computers to identify patterns, make predictions, or take actions based on provided data. In essence, machine learning grants computers the ability to "learn" from experience or data and use this knowledge to handle new situations or similar tasks. This process is carried out through convolution, where a filter is slid across the entire area of an image to recognize existing patterns. Face detection and attendance systems have become compelling topics in the fields of computer vision and security. In today's digital era, the use of automated systems to recognize faces and monitor attendance is increasingly vital across various sectors, including education, business, and security. Research on the development of face detection and attendance systems utilizes the Python programming language and OpenCV (Open Source Computer Vision Library). Python is a popular programming language with numerous libraries supporting computer vision development, while OpenCV provides various functions and algorithms useful for image analysis and processing. Face detection and attendance systems built with Python and OpenCV hold great potential for increasing efficiency and accuracy in the attendance process, as well as minimizing misuse or fraud. Therefore, in its implementation, it is essential to consider appropriate privacy policies and data protection measures to ensure the technology is used ethically and in compliance with applicable laws. Through this research, it is expected that readers will gain a better understanding of face detection.]]>
Copyrights © 2026
