• Dr Seshaiah Merikapudi
• Supriya D
• Swathi G

People now living in a world of corporate culture like workplaces and colleges, schools, hospitals. In particular educational institutions will ensure the students to maintain dress code to obtain uniformity among the students. It is a difficult task to the management to identify the students who doesn’t follow the dress code. To observe manually it requires more human involvement and it is not possible for the entire day. To overcome across those issues, the proposed model presents a neural network based classification system to identify and differentiate the students. Systematic learning of analytics is becoming an essential topic in the educational area, in which requires effective systems to monitor the learning process and provides feedback to the staff. The software records the entire session and identifies when the students pay attention in the classroom, and then reports to the facilities. In this paper we want to deviate from the old approach and go with the new approach by using techniques that are there in image processing. Here in this paper we representing spontaneous presence for students in classroom

Convolution neutrals, Pooling, Flattened, Fully Connected, Visual attention, Digital Attendance

"Recognizing Students Through Surveillance System Using Different Recognition Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.b74-b85, June-2022, Available :http://www.jetir.org/papers/JETIR2206113.pdf

"Recognizing Students Through Surveillance System Using Different Recognition Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppb74-b85, June-2022, Available at : http://www.jetir.org/papers/JETIR2206113.pdf