Volume 2 , Issue 2 , April 2022

Face Recognition based on Convoluted Neural Networks: Technical Review

Basil Ismail Mirghani Shakkak
Sohar University FCIT
Sohar University, FCIT , Sohar, Oman.


Human beings recognize and classify objects with biological senses and brain that processes the input into meaningful information. Other than that humans have come to recognize each other in multiple ways one of which is visual recognition of faces. As a biological trait human faces are certainly a biometric such they are universal, distinctive, mostly permanent and collectable. With that a computerized face recognition system can constructed relying on visual information present on each face uniquely. Generally a face recognition system consists of two main phases, face detection phase where presence of a human face is verified on visual input and face recognition phase where detected face is processed for identification. One of the most sought after methods in field image processing for face recognition is CNN (Convoluted Neural Networks). CNNs have proved its effectiveness and accuracy in many CNN based face detection and face recognition systems. As such in this paper the architecture of CNN is presented. Then different techniques for face detection and face recognition based on CNNs are reviewed. In reviewed papers CNNs have repeatedly demonstrated effectiveness and accuracy on multiple benchmarks for face recognition application.


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Published April 16, 2022
How to Cite
Shakkak, B. I. M., & SARA ALI K. M. AL MAZRUII. (2022). Face Recognition based on Convoluted Neural Networks: Technical Review. Applied Computing Journal, 2(2), 193-212. https://doi.org/10.52098/acj.202247