Auto Detection of Attendance Based on Deep Learning

Dr.P.Lalitha Kumari,B.Dharani, K.Kesav Sai Kumar,K. Sivaku mar,N.charan ,B.Mohan
i Associate Professor, Computer Science and Engineering, Visakha Institute Of Engineering &
2,3,4,5 B Tech Student,Computer Science & Engineering, Visakha Institute Of
Engi neering and Technology(A), Narava,Visakhapatnam , 530027, India

Abstract:The Auto Detection Of Attendance based on Deep Learning is an advanced system that automates the process of attendance marking using facial recognition technology. Traditional methods such as manual registers and ID card systems are time-consuming, error-prone, and allow proxy attendance. This project introduces an intelligent solution that uses cameras and image processing techniques to capture and analyze facial features, ensuring accurate and efficient attendance recording without human interventiom The system utilizes powerful models like Convolutional Neural Network (CNN) to detect and recognize faces from real time video streams. initially, a dataset of facial images is collected and used to train the model. During operation, the system detects faces, extracts unique features, and compares them with stored data to identify individuals. Once a match is confirmed, attendance is automatically marked with date and time, and the information is securely stored in a database. This approach significantly reduces manual effort, enhances accuracy, and provides a contactlesg solution suitable for modern environments. It can be effectively implemented in schools, colleges, offices, and organizations where reliable attendance tracking is required. The integration of deep learning not only improves system performance but also ensuresscalability and adaptability for future advancements, making it a practical and efficient solution for real-world applications.Keywords:Auto Attendance System, Deep Learning, Face Recognition, Convolutional Neural