FACE DETECTION SYSTEM USING CONVOLUTIONAL NEURAL NETWORKS: A REVIEW

 FACE DETECTION SYSTEM USING CONVOLUTIONAL NEURAL NETWORKS: A REVIEW

Mr. Jai Desai, Mr. Ujwal Pedhekar, Mr. Atharva Sarode, Ms. Revati Ramteke,

Ms. Rasika Shelke, Prof. A.D Shah

“Department of Computer Science”

Sipna College of Engineering and Technology Amravati Maharashtra

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Abstract

 Implementing a facial recognition system can help in identifying or verifying the identity of a person from a digital image. Accurate attendance records are critical to classroom assessment. However, manual attendance tracking can lead to errors, missed students, or duplicate records. The facial recognition attendance system includes facial recognition technology that recognizes and verifies an employee's facial features and automatically records attendance.

The facial liveliness detection part is based on CNN, which creates a 3D model of the detected face to distinguish between real and fake images. The attendance system is written in Python and the user interface is designed using the WebView library. The main goal of facial recognition is to identify individuals, either individually or collectively. The number of positive faces may vary depending on the technology used for face recognition.

Keywords: Face Recognition Attendance System, CNN Algorithm.