• GANDHAM SAI TEJA
• CHELLEM NARASIMHA MURTHY
• CHALLA MANEESH GOWTHAM
• DURBHA V R L N D S S H KALI VARA PRASAD
• Dr K KISHORE RAJU

Through the use of convolutional neural networks (CNNs), a deep learning approach, this research seeks to improve security by enabling people to authenticate themselves in front of a camera. The system shows the name and other details of an authorized user after identifying them from a pre-existing database. But in the event that a person is recognized as unauthorized, the system makes use of pre-trained algorithms to forecast and present the person's age, gender, and emotional state. The technology additionally includes a beep sound to notify security workers of unlawful attempts. This dual functionality collects useful demographic information on unauthorized attempts in addition to strengthening security measures by limiting access to authorized users exclusively. With increased security and user privacy guaranteed, the project responds to the growing need for reliable and effective authentication mechanisms in contemporary applications.

CNN , DLIB , HAAR CASCADE CLASSIFIER

"Human Authentication System Using Deep learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.h82-h86, April-2024, Available :http://www.jetir.org/papers/JETIR2404711.pdf

"Human Authentication System Using Deep learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. pph82-h86, April-2024, Available at : http://www.jetir.org/papers/JETIR2404711.pdf