• Ashish Dusane
• Mrs. Vineeta Tiwari
• Mr. Manish Nirmal
• Dr. Bhushan Chaudhari

Future Smart Classroom that we envision will significantly enhance learning experience and seamless communication among students and teachers using real-time sensing and machine intelligence. In that, we research a Smart Classroom system that consists of these components like Student Attendance using Facial Recognition algorithms, human behavior, such as hand gestures, facial expressions and body language, Sentiment Analysis based of Student behavior. We base our suggested system components on existing research in deep learning-based Emotion / Behavior recognition. In this paper comprehensive study of the process of deep learning-based Emotion / Behaviour recognition has been done and determining the computational requirements of a system that incorporates these technologies. Based on these requirements, we research a study of the system like: i) Smart classroom automatic attendance system by using two deep learning facial recognition algorithms Convolutional Neural Network (CNN). ii) Behavior Analysis Model Based on Facial Recognition using Convolutional Neural Network (CNN).

Face Detection, Face Recognition, Face Identification, Behavior Analysis, CNN.

"Face Recognition Based Attendance System Using Convolutional Neural Network (CNN) For Human Behavior Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.788-800, June-2019, Available :http://www.jetir.org/papers/JETIR1906D26.pdf

"Face Recognition Based Attendance System Using Convolutional Neural Network (CNN) For Human Behavior Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp788-800, June-2019, Available at : http://www.jetir.org/papers/JETIR1906D26.pdf