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1

Deshmukh, Sagar, Sanjay Rawat, and Shubhangi Patil. "Face Recognition Technology." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (2018): 1612–13. http://dx.doi.org/10.31142/ijtsrd14331.

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2

Yadav, Rakeshkumar H., Brajgopal Agarwal, and Sheeba James. "Face Recognition System." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (2018): 1815–18. http://dx.doi.org/10.31142/ijtsrd14453.

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3

Ounachad, Khalid, Mohamed Oualla, Abdelalim Sadiq, and Abdelghani Sohar. "Face Sketch Recognition: Gender Classification and Recognition." International Journal of Psychosocial Rehabilitation 24, no. 03 (2020): 1073–85. http://dx.doi.org/10.37200/ijpr/v24i3/pr200860.

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4

V, Prathama, and Thippeswamy G. "Age Invariant Face Recognition." International Journal of Trend in Scientific Research and Development Volume-3, Issue-4 (2019): 971–76. http://dx.doi.org/10.31142/ijtsrd23572.

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5

Lakshmi, Dr D. Vijaya, Srija Reddy Ardha, and Anand karthik Azmeera. "Cross Age Face Recognition." International Journal of Research Publication and Reviews 6, no. 4 (2025): 4381–407. https://doi.org/10.55248/gengpi.6.0425.1466.

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6

Rakeshkumar, H. Yadav, Agarwal Brajgopal, and James Sheeba. "Face Recognition System." International Journal of Trend in Scientific Research and Development 2, no. 4 (2018): 1815–18. https://doi.org/10.31142/ijtsrd14453.

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Face is a important part through which we can identify who we are and how people identify us. Face is a persons most valuable and unique physical characteristics through which we can identify someone very easily. While humans have the innate ability to distinguish the different faces for millions of years for adding the new technology computers are just now catching up. A face recognition system is a computer application that is capable of identifying or verifying the person from a digital image or a video frame from video source. One of the way is to do this is by compare with the selected fa
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Telugu, Maddileti, Shriphad Rao G., Sai Madhav Vaddemani, and Sharan Ganti. "Home Security using Face Recognition Technology." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 2 (2019): 678–82. https://doi.org/10.35940/ijeat.B3917.129219.

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Face is the easiest way to penetrate each other's personal identity. Face recognition is a method of personal identification using the personal characteristics of an individual to decide the identification of a person. The method of human face recognition consists basically of two levels, namely face detection and face recognition. There are three types of methods that are currently popular in the developed face recognition pattern, those are Eigen faces algorithm, Fisher faces algorithm and CNN neural network for face recognition
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Patel, Ibrahim, Raghavendra Kulkarni, and Dr P. Nageswar Rao. "Robust Singular Value Decomposition Algorithm for Unique Faces." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, no. 2 (2018): 596–603. http://dx.doi.org/10.24297/ijct.v4i2c1.4178.

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It has been read and also seen by physical encounters that there found to be seven near resembling humans by appearance .Many a times one becomes confused with respect to identification of such near resembling faces when one encounters them. The recognition of familiar faces plays a fundamental role in our social interactions. Humans are able to identify reliably a large number of faces and psychologists are interested in understanding the perceptual and cognitive mechanisms at the base of the face recognition process. As it is needed that an automated fa
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Reddy, Mr B. Ravinder, V. Akhil, and G. Sai Preetham P. Sai Poojitha. "Profile Identification through Face Recognition." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (2019): 1482–83. http://dx.doi.org/10.31142/ijtsrd23439.

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10

A, ASLIM S., and Dr A. MYTHILI. "Automation Attendance Using Face Recognition." International Journal of Research Publication and Reviews 6, no. 4 (2025): 257–60. https://doi.org/10.55248/gengpi.6.0425.1314.

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11

Aishwarya, T. G., Veena N, and Pallerla Asritha. "Face Recognition Attendance Management System." International Journal of Research Publication and Reviews 6, no. 5 (2025): 11049–52. https://doi.org/10.55248/gengpi.6.0525.1888.

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12

Garg, Deepika. "Face Recognition." IOSR Journal of Engineering 02, no. 07 (2012): 128–33. http://dx.doi.org/10.9790/3021-0271128133.

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13

Zhao, W., R. Chellappa, P. J. Phillips, and A. Rosenfeld. "Face recognition." ACM Computing Surveys 35, no. 4 (2003): 399–458. http://dx.doi.org/10.1145/954339.954342.

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14

Gross, Charles G., and Justine Sergent. "Face recognition." Current Biology 2, no. 5 (1992): 235. http://dx.doi.org/10.1016/0960-9822(92)90354-d.

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15

.Gross, Charles G., and Justine Sergent. "Face recognition." Current Opinion in Neurobiology 2, no. 2 (1992): 156–61. http://dx.doi.org/10.1016/0959-4388(92)90004-5.

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16

Prof Sami M. Halwani, Prof M. V. Ramana Murthy, and Prof S. B. Thorat. "Laplacian Faces: A Face Recognition Tool." International Journal of Networked Computing and Advanced Information Management 2, no. 1 (2012): 1–7. http://dx.doi.org/10.4156/ijncm.vol2.issue1.1.

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17

Schwartz, Linoy, and Galit Yovel. "Are Faces Important for Face Recognition?" Journal of Vision 15, no. 12 (2015): 703. http://dx.doi.org/10.1167/15.12.703.

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18

Tovée, Martin J. "Face Recognition: What are faces for?" Current Biology 5, no. 5 (1995): 480–82. http://dx.doi.org/10.1016/s0960-9822(95)00096-0.

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19

He, Yunhui, Li Zhao, and Cairong Zou. "Face recognition using common faces method." Pattern Recognition 39, no. 11 (2006): 2218–22. http://dx.doi.org/10.1016/j.patcog.2006.04.037.

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20

米, 勇. "Face Recognition Based on Feature Faces." Computer Science and Application 09, no. 01 (2019): 127–31. http://dx.doi.org/10.12677/csa.2019.91015.

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21

C.G., Ezekwe I. C. Ituma P. I. Okwu. "FACE PROCESSING AND RECOGNITION BASED CLASSROOM ATTENDANCE SYSTEM." Global Journal of Engineering Science and Research Management 5, no. 4 (2018): 12–23. https://doi.org/10.5281/zenodo.1222126.

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Educational institutions’ administrators in our country and the whole world are concerned about regularity of student attendance. Student overall academic performance is affected by it. The conventional method of taking attendance by calling names or signing on paper is very time consuming, and hence inefficient. This problem gave birth to research on Radio frequency identification (RFID) authentication with face processing and recognition though in this paper we basically highlighted on the face processing and recognition. The system is made up of a camera which take the photos of indiv
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22

Xiong, Yijie. "Face recognition based on machine learning." Applied and Computational Engineering 6, no. 1 (2023): 1100–1105. http://dx.doi.org/10.54254/2755-2721/6/20230407.

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Due to its widespread use, face recognition has emerged in the past 20 years as one of the most pervasive biometric identification technology disciplines. This paper briefly summarizes the history of face recognitions development, identifies the technologys present use cases, introduces the main methods of face recognition in detail from the perspective of machine learning and prospects for the future development of this technology. The result shows that this technology still faces many challenges, such as the problem of recognizing different expressions on the same face, the problem of recogn
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23

Sagar, Deshmukh, Rawat Sanjay, and Patil Shubhangi. "Face Recognition Technology." International Journal of Trend in Scientific Research and Development 2, no. 4 (2019): 1612–13. https://doi.org/10.31142/ijtsrd14331.

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The biometric is a study of human behavior and features. Face recognition is a technique of biometric. Various approaches are used for it. Face recognition is emerging branch of biometric for security as no faces can be defeated as a security approach. So, how we can recognize a face with the help of computers is given in this paper. The typical way that a FRS can be used for identification purposes. The effectiveness of the whole system is highly dependent on the quality and characteristics of the captured face image. The process begins with face detection and extraction from the larger image
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24

Afrin, Sadia, Maria Tasnim, and Md Rafiqul Islam. "Human Face Recognition Using Eigen Vector-Based Recognition System." International Journal of Research and Scientific Innovation X, no. VI (2023): 127–34. http://dx.doi.org/10.51244/ijrsi.2023.10617.

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Face recognition is an algorithm that can recognize or verify a query face among a large number of faces in the enrollment database. Face recognition is a crucial and difficult area of computer vision. This study demonstrates a system that can recognize a human face by comparing the facial structure to that of another individual or a well-known individual, which is accomplished by the use of frontal several summarizations. Many researchers have done their work on face recognition and also applied it by using different methods. We made use of an eigenvector-based recognition system as a method
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Anjali, Muneshwar, and Vattam Prof.Jayarajesh. "Face Detection System with Face Recognition." International Organization of Research & Development (IORD) 9, no. 1 (2021): 5. https://doi.org/10.5281/zenodo.5016190.

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The face is one of the easiest ways to distinguish the individual identity of each other. Face recognition is a personal identification system that uses the personal characteristics of a person to identify the person's identity. The human face recognition procedure basically consists of two phases, namely face detection, where this process takes place very rapidly in humans, except under conditions where the object is located at a short distance away, the next is the introduction, which recognizes a face as individuals. The stage is then replicated and developed as a model for facial image
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Kaur, Puneet. "Exploring the Challenges of Aadhaar based Face Recognition in Unrestricted Environments." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem41021.

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- Technology improvements have resulted in a high criminal rate, which has raised serious concerns about security-related issues. Face recognition can be used to identify people because every person tends to possess a particular attribute. One of the main applications of facial recognition is in the field of video surveillance. To reduce the increasing criminal rates, this technology is responsible for extracting features from the human face and further identifying them. The CCTV footage might also be used to identify suspects at a crime scene. However, the criminals would be found by recogniz
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27

Abbas, Hawraa H., Bilal Z. Ahmed, and Ahmed Kamil Abbas. "3D Face Factorisation for Face Recognition Using Pattern Recognition Algorithms." Cybernetics and Information Technologies 19, no. 2 (2019): 28–37. http://dx.doi.org/10.2478/cait-2019-0013.

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Abstract The face is the preferable biometrics for person recognition or identification applications because person identifying by face is a human connate habit. In contrast to 2D face recognition, 3D face recognition is practically robust to illumination variance, facial cosmetics, and face pose changes. Traditional 3D face recognition methods describe shape variation across the whole face using holistic features. In spite of that, taking into account facial regions, which are unchanged within expressions, can acquire high performance 3D face recognition system. In this research, the recognit
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Priya, B. Lakshmi, and Dr M. Pushpa Rani Rani. "Face Recognition System Techniques and Approaches." Indian Journal of Applied Research 4, no. 4 (2011): 109–13. http://dx.doi.org/10.15373/2249555x/apr2014/32.

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29

R.S., Dr Sabeenian. "Attendance Authentication System Using Face Recognition." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (2020): 1235–48. http://dx.doi.org/10.5373/jardcs/v12sp4/20201599.

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30

Mishra, K. Ravikanth, D. Brahmeswara Rao, and A. Dinesh Chowdary. "Student Library Attendance using Face Recognition." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 1238–40. http://dx.doi.org/10.31142/ijtsrd11281.

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31

Malkapurkar, Anagha V., and Prof Sachin Murarka. "Using LBP histogram for Face Recognition." International Journal of Scientific Research 1, no. 7 (2012): 176–77. http://dx.doi.org/10.15373/22778179/dec2012/64.

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32

Kanth, Pooja L., and Salva Biswal. "Attendance Marking System Using Face Recognition." Indian Journal of Science and Technology 12, no. 48 (2019): 1–3. http://dx.doi.org/10.17485/ijst/2019/v12i48/145821.

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33

Dhaygude, Rohit H., Avinash M. Gaikwad, Suraj Y. Gawali, and Prof Jawed H. Shaikh. "Smart Home Security & Face Recognition." International Journal of Research Publication and Reviews 5, no. 4 (2024): 4009–13. http://dx.doi.org/10.55248/gengpi.5.0424.1023.

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34

Rhodes, Gillian. "Adaptive Coding and Face Recognition." Current Directions in Psychological Science 26, no. 3 (2017): 218–24. http://dx.doi.org/10.1177/0963721417692786.

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Face adaptation generates striking face aftereffects, but is this adaptation useful? The answer appears to be yes, with several lines of evidence suggesting that it contributes to our face-recognition ability. Adaptation to face identity is reduced in a variety of clinical populations with impaired face recognition. In addition, individual differences in face adaptation are linked to face-recognition ability in typical adults. People who adapt more readily to new faces are better at recognizing faces. This link between adaptation and recognition holds for both identity and expression recogniti
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Bhange, Prof Anup. "Face Detection System with Face Recognition." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 1095–100. http://dx.doi.org/10.22214/ijraset.2022.39976.

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Abstract: The face is one of the easiest way to distinguish the individual identity of each other. Face recognition is a personal identification system that uses personal characteristics of a person to identify the person's identity. Now a days Human Face Detection and Recognition become a major field of interest in current research because there is no deterministic algorithm to find faces in a given image. Human face recognition procedure basically consists of two phases, namely face detection, where this process takes place very rapidly in humans, except under conditions where the object is
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36

Romanyuk, Olexandr N., Sergey I. Vyatkin, Sergii V. Pavlov, Pavlo I. Mykhaylov, Roman Y. Chekhmestruk, and Ivan V. Perun. "FACE RECOGNITION TECHNIQUES." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 10, no. 1 (2020): 52–57. http://dx.doi.org/10.35784/iapgos.922.

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The problem of face recognition is discussed. The main methods of recognition are considered. The calibrated stereo pair for the face and calculating the depth map by the correlation algorithm are used. As a result, a 3D mask of the face is obtained. Using three anthropomorphic points, then constructed a coordinate system that ensures a possibility of superposition of the tested mask.
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37

Said, Ebrahem, and Mona Nasr. "Face Recognition System." International Journal of Advanced Networking and Applications 12, no. 02 (2020): 4567–74. http://dx.doi.org/10.35444/ijana.2020.12205.

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38

Rajput, Ankit. "Face Recognition Technology." International Journal for Research in Applied Science and Engineering Technology 7, no. 3 (2019): 859–62. http://dx.doi.org/10.22214/ijraset.2019.3150.

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39

Sabharwal, Himani, and Akash Tayal. "Human Face Recognition." International Journal of Computer Applications 104, no. 11 (2014): 1–3. http://dx.doi.org/10.5120/18243-9173.

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40

Liu, Tongyang, Xiaoyu Xiang, Qian Lin, and Jan P. Allebach. "Face Set Recognition." Electronic Imaging 2019, no. 8 (2019): 400–1. http://dx.doi.org/10.2352/issn.2470-1173.2019.8.imawm-400.

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41

Saxenna, Yasharth. "Face Recognition System." International Journal for Research in Applied Science and Engineering Technology 8, no. 7 (2020): 1883–85. http://dx.doi.org/10.22214/ijraset.2020.30704.

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42

Tang, X., and X. Wang. "Face Sketch Recognition." IEEE Transactions on Circuits and Systems for Video Technology 14, no. 1 (2004): 50–57. http://dx.doi.org/10.1109/tcsvt.2003.818353.

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43

S.G, Rajeshwari. "Human Face Recognition." International Journal for Research in Applied Science and Engineering Technology 8, no. 6 (2020): 638–43. http://dx.doi.org/10.22214/ijraset.2020.6104.

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44

Dzhangarov, A. I., M. A. Suleymanova, and A. L. Zolkin. "Face recognition methods." IOP Conference Series: Materials Science and Engineering 862 (May 28, 2020): 042046. http://dx.doi.org/10.1088/1757-899x/862/4/042046.

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Liu, Yun-Fu, Jing-Ming Guo, Po-Hsien Liu, Jiann-Der Lee, and Chen-Chieh Yao. "Panoramic Face Recognition." IEEE Transactions on Circuits and Systems for Video Technology 28, no. 8 (2018): 1864–74. http://dx.doi.org/10.1109/tcsvt.2017.2693682.

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46

Moghaddam, Baback, Tony Jebara, and Alex Pentland. "Bayesian face recognition." Pattern Recognition 33, no. 11 (2000): 1771–82. http://dx.doi.org/10.1016/s0031-3203(99)00179-x.

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47

Russell, R., B. Duchaine, and K. Nakayama. "Extraordinary face recognition." Journal of Vision 7, no. 9 (2010): 629. http://dx.doi.org/10.1167/7.9.629.

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48

Voth, D. "Face recognition technology." IEEE Intelligent Systems 18, no. 3 (2003): 4–7. http://dx.doi.org/10.1109/mis.2003.1200719.

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49

Bruce, Vicki, and Andy Young. "Understanding face recognition." British Journal of Psychology 77, no. 3 (1986): 305–27. http://dx.doi.org/10.1111/j.2044-8295.1986.tb02199.x.

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Kroeker, Kirk L. "Face recognition breakthrough." Communications of the ACM 52, no. 8 (2009): 18–19. http://dx.doi.org/10.1145/1536616.1536623.

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