Deep Learning approach for Minimizing Disease Spread using Face Identification and Contact Tracing

Convolutional Neural system arrangement for anticipating the likelihood of relationship of a person with others in a social affair is the main objective of this paper. The framework joins the convolutional neural system and AI calculations. The coordinated applications are face identification, face bunching and face identifier. This technique is fit for quick order and gives preferred execution over the eigenfaces approach. The DLIB calculation encodes the face into 128D exhibit and stores it in record taking care of framework. The framework accepts video as source and employments face acknowledgment Chinese murmur bunching calculation to group the essences of a person. In view of the information from the bunch results, the apriori/affiliation rule mining calculation finds the affiliated likelihood. The framework is coordinated with google cloud to give application-based interface which makes application programming interface calls. Association rule mining algorithm is used to find the confidence probabilities of a person with other individuals of the video clipping.