AMDM-DL: Automatic Mask Detection Mechanism in CC Tv Footage Using Deep Learning

Prof Kiran Sree Pokkuluri; Smt. SSSN Usha Devi .N

Prof Kiran Sree Pokkuluri Professor Dept of CSE BVC Engineering College, India
Smt. SSSN Usha Devi .N Assistant Professor, Dept of CSE, University College of Engineering, JNTU-Kakinada

Abstract

The world has witnessed the most dangerous virus named as COVID-19. Many people have been suffering from this pandemic, and many measures are taken to minimize the effect of the virus. The use of masks is one of the preventive methods suggested to reduce the spreading of the virus. A deep convolution neural network (DCNN)is developed to address the problem DCNN robust and effective mechanism to monitor the usage of masks from CC Tv footage. AMDM-DL is trained and tested with 36, 21, 004 videos [1]. We have measured the effectiveness of the method with parameters such as accuracy, precision, and sensitivity. AMDM-DL has reported an accuracy of 89.36 with precision, sensitivity values as 0.92, 0.95, respectively.

How to cite this article:
Sree PK, Usha Devi NSSSN. AMDM-DL: Automatic Mask Detection Mechanism in CC Tv Footage Using Deep Learning. J Adv Res Appl Arti Intel Neural Netw 2020; 4(2): 1-3.

Author Biography

Prof Kiran Sree Pokkuluri, Professor Dept of CSE BVC Engineering College, India

drkiransree@gmail.com

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