Deep Learning Based Intelligent Screening Mechanism
2022 International Conference on Communication, Computing and Internet of Things, IC3IoT 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-1874253
ABSTRACT
Facial recognition is widely used for identification of people as one of the biometric authentications. Biometric authentication consists of two types physiological and behavioral features. In physiological biometrics, faces, iris, and fingerprints are used for identifying the person. In behavioral biometrics, their characteristic features namely voice, DNA and hand writing is used. While using facial recognition, an individual can be identified using the previously trained model using deep learning based on the Haar cascade algorithm. Biometric authentication has been generally used for surveillance purposes. However, due to the COVID 19 pandemic, people of each nation are in need to wear face masks for their safety. Our project uses deep learning and open cv to recognize the person and to identify whether he wears a face mask or not by using transfer learning techniques and convolution neural network. One large dataset of people with mask and people without a mask was used as a training model. Our project was able to achieve an accuracy of 96.8% during the training and testing phase. © 2022 IEEE.
Convolution neural networks; Face mask detection; Face recognition; Haer cascade Algorithm; Transfer Learning; Authentication; Biometrics; Convolution; Deep learning; Large dataset; Learning algorithms; Physiology; Biometric authentication; Cascade algorithm; Convolution neural network; Face masks; Facial recognition; Intelligent screenings; Screening mechanism
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2022 International Conference on Communication, Computing and Internet of Things, IC3IoT 2022
Year:
2022
Document Type:
Article
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