Face recognition using haar cascade classifier andFaceNet (A case study: Student attendance system)

Abstract

Face recognition is increasingly widely utilised, and there are numerous face recognition systems. Face recognition is typically utilised for attendance on e-learning platforms in the field of education. The haar cascade classifier is one  method  for  face  identification;  it  is  used  to  identify  facial  areas.  Faces are  classified  using  an  alternative  model,  FaceNet.  In  this  research,  we purposefully  designed  an  e-learning  platform  that  authenticates  students based  on  face  recognition.  Based  on  the  findings  of this  investigation,  the system can accurately recognise faces. Ten students were evaluated based on their  participation  in  two  attendance  trials.  Successful  presence  has  an achievement success value of 19, and 1 failed out of a total of 20 attempts. Several  variables,  such  as  illumination,  and  the  use  of  marks  on  hats,  that could have influenced attendance caused the experiment to fail.