1、Table of ContentsHow Deep Learning Upgrades Face Recognition SoftwareLIMITATIONS OF THE TRADITIONAL APPROACH TO FACIAL RECOGNITIONAI-ENHANCED FACE RECOGNITIONHighlights of AI face recognition system softwareHOW FACE RECOGNITION WORKSFace recognition accuracy and how to improve itConclusion1Biometric

2、 identification of a person by facial features is increasingly usedto solve business and technical issues.The development of relevant automatedsystems or the integration of such tools into advanced applications has becomemuch easier.First of all,this is caused by the significant progress in AI facer

3、ecognition.In this article,we will explain what the components are of a facerecognition software and how to overcome the limitations and challenges ofthese technologies.You will find out how AI,namely Deep Learning,can improve the accuracyand performance of face recognition software,and how,thanks t

4、o this,it ispossible to train an automated system to correctly identify even poorly lit andchanged faces.It will also become clear what techniques are used to trainmodels for face detection and recognition.Do you remember trying to unlock something or validate that its you,with thehelp of a selfie y

5、ou have taken,but lighting conditions didnt allow you to dothat?Do you wonder how to avoid the same problem when building your appwith a face recognition feature?How Deep Learning Upgrades FaceRecognition SoftwareTraditional face recognition methods come from using eigenfaces to form abasic set of i

6、mages.They also use a low-dimensional representation of imagesusing algebraic calculations.Then the creators of the algorithms moved indifferent ways.Part of them focused on the distinctive features of the faces andtheir spatial location relative to each other.Some experts have also researchedhow to