A Face Recognition Security Model Using Transfer Learning Technique Pdf Conceptual Model

By switzerlandersing On Sep 16, 2025

A_Face_Recognition_Security_Model_Using_Transfer_Learning_Technique | PDF | Deep Learning ...

A_Face_Recognition_Security_Model_Using_Transfer_Learning_Technique | PDF | Deep Learning ... A face recognition security model using transfer learning technique published in: 2022 8th international conference on smart structures and systems (icsss) article #: date of conference: 21 22 april 2022. This paper presents a face detection system with expression recognition using artificial neural networks. it is an automated vision system designed and implemented using matlab.

Face Recognition | PDF | Cloud Computing | Cryptography

Face Recognition | PDF | Cloud Computing | Cryptography Many organizations use facial recognition as a means of authentication. researchers focus on developing rapid and efficient solutions to deal with the ongoing coronavirus pandemic by coming up with suggestions for handling the facial recognition problem. We employ the transfer learning technique to efectively train our proposed deep cnn model and mitigate overfitting. our proposed system successfully addresses the challenges associated with unconstrained conditions and training deep learning models using limited datasets. Here, model is pre trained with the person's face and a mask is introduced to the model to recognize a masked face. yolo objection detection technique was chosen for this paper. Face recognition (fr) is a technique for recognizing individuals through the use of face photographs. the fr technology is widely applicable in a variety of fields, including security, biometrics, authentication, law enforcement, smart cards, and surveillance.

Face Recognition Using Transfer Learning. | By Abhiney Singh | Medium

Face Recognition Using Transfer Learning. | By Abhiney Singh | Medium Here, model is pre trained with the person's face and a mask is introduced to the model to recognize a masked face. yolo objection detection technique was chosen for this paper. Face recognition (fr) is a technique for recognizing individuals through the use of face photographs. the fr technology is widely applicable in a variety of fields, including security, biometrics, authentication, law enforcement, smart cards, and surveillance. We have applied a transfer learning model based on alexnet deep functionality can occasionally outperform human learning application to develop a real time facial recognition performance. Abstract—security based applications seek face biometrics as an integral part of the biometrics system which is susceptible to spoof attacks. a malicious person can gain unauthorized access to any system by displaying a picture or video of the registered user’s face. In this paper we proposed the face recognition system using inception v3 model of tensorflow platform based on transfer learning approach to train cnn model. after performing all experiments the results obtained from our proposed system recognized the human face images well. In 2007, labeled faces in the wild was released in an effort to spur research in face recognition, specifically for the problem of face verification with unconstrained images.

(PDF) Face Recognition And Verification Using Transfer Learning

(PDF) Face Recognition And Verification Using Transfer Learning We have applied a transfer learning model based on alexnet deep functionality can occasionally outperform human learning application to develop a real time facial recognition performance. Abstract—security based applications seek face biometrics as an integral part of the biometrics system which is susceptible to spoof attacks. a malicious person can gain unauthorized access to any system by displaying a picture or video of the registered user’s face. In this paper we proposed the face recognition system using inception v3 model of tensorflow platform based on transfer learning approach to train cnn model. after performing all experiments the results obtained from our proposed system recognized the human face images well. In 2007, labeled faces in the wild was released in an effort to spur research in face recognition, specifically for the problem of face verification with unconstrained images.