Face Detection system using deep learning and CNN Algorithm

Registration ID: IJNRD_218445

Published ID: IJNRD2404613

DOI: Click Here to Get

Jai Desai , Ujwal pedhekar , Rasika Shelke , Atharva Sarode , Revati H. Ramteke,Prof. A.D. Shah

1. Face Detection 2. Convolutional neural network 3. Deep learning 4. Facial Recognition

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 Implementing a facial recognition system can help in identifying 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.

Published Paper   E-Certificate

Jai Desai, Ujwal pedhekar , Rasika Shelke, Atharva Sarode, & Revati H. Ramteke,Prof. A.D. Shah (April-2024). Face Detection system using deep learning and CNN Algorithm . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), g134-g143. https://ijnrd.org/papers/IJNRD2404613.pdf

Volume 9 Issue 4, April-2024

Pages : g134-g143

Paper Reg. ID: IJNRD_218445

Published Paper Id: IJNRD2404613

Downloads: 000121978

Research Area: Computer Engineering 

Country: Amravati , Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404613.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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