Categorizing the students’ activities for automated exam proctoring using proposed deep l2-graftnet cnn network and aso based feature selection approach

HIGHLIGHTS

• who: TANZILA SABA and collaborators from the Intelligence and Data Analytics Lab (AIDA), College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi have published the article: Categorizing the Students’ Activities for Automated Exam Proctoring Using Proposed Deep L2-GraftNet CNN Network and ASO Based Feature Selection Approach, in the Journal: (JOURNAL)
• what: The authors propose an integrated exam control solution, focused on surveillance, that offers an automatic categorization of the behavior and activities of students during exams. The images captured from the webcam are subtracted with the reference image and if the . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.