Find Your Missing Child Using Face Authentication

Abstract

In India, There Are Numerous Children Missing Each Year. A Significant Proportion Of Youngsters Remain Untracked Among The Missing Children. This Article Provides A Newness Of The Technique Of Deep Learning To Detect The Reported Missing Kid From The Photographs Of Many Accessible Youngsters Using Facial Recognition. The Public May Submit Worrisome Kid Photos Onto A Shared Site With Monuments And Comments. The Picture Is Immediately Matched To The Photographs Of The Missing Kid In The Repository. The Supplied Kid Picture Is Classified And The Best Match Photo Is Chosen From The Missing Children's Database. For This Purpose, A Deep Learning Model Is Built In Order To Properly Identify The Missing Kid From The Missing Picture Database Supplied Using Publicly Submitted Face Images. For Face Identification, The Convolution Neural Network (CNN) Is A Very Efficient Deep Learning Method For Image-Based Applications. Face Descriptors Are Retrieved Utilizing The Deep Architecture Of A Previously Trained CNN VGG-Face Model. Our Algorithm Utilizes A Convolution Network Just As A High Level Feature Extractor In Comparison With Conventional Deep Learning Applications. The Kid Identification Is Done By The Trained KNN Classifier. Choosing The Best-Performing CNN Model To Recognize The Face, VGG-Face, And Appropriate Training Leads In A Profound Learning Model That Is Invariant In The Child's Noise, Lighting, Contrast, Occlusion, Picture Poses And Age, And Outputs Previous Techniques For The Identification Of Missing Children.