With the advancing technology, the hardware gain of computers and the increase in the processing capacity of processors have facilitated the processing of instantaneous and real-time images. Face recognition processes are also studies in the field of image processing. Facial recognition processes are frequently used in security applications and commercial applications. Especially in the last 20 years, the high performances of artificial intelligence (AI) studies have contributed to the spread of these studies in many different fields. Education is one of them. The potential and advantages of using AI in education; can be grouped under three headings: student, teacher, and institution. One of the institutional studies may be the security of educational environments and the contribution of automation to education and training processes. From this point of view, deep learning methods, one of the sub-branches of AI, were used in this study. For object detection from images, a pioneering study has been designed and successfully implemented to keep records of students' entrance to the educational institution and to perform class attendance with images taken from the camera using image processing algorithms. The application of the study to real-life problems will be carried out in a school determined in the 2022-2023 academic year.

翻译：随着技术的进步，计算机硬件性能的提升以及处理器处理能力的增强，为实时图像的处理提供了便利。人脸识别技术也是图像处理领域的研究方向之一。人脸识别技术广泛应用于安全应用和商业应用中，尤其是近二十年来，人工智能（AI）研究的高性能表现推动了这些研究在诸多不同领域的普及。教育领域便是其中之一。人工智能在教育领域的应用潜力与优势可从三个方面归纳：学生、教师与机构。机构层面的研究之一可能涉及教育环境的安全保障以及自动化对教与学过程的促进作用。基于此，本研究采用了人工智能分支之一的深度学习方法。针对从图像中检测对象，我们设计了一项开创性研究，并成功实现了利用图像处理算法通过摄像头拍摄的图像记录学生进入教育机构的记录以及进行课堂考勤。该研究在实际问题中的应用将于2022-2023学年在一所选定学校中实施。