The facial information of a person has constant invariance, and at the same time, it is an ideal basis for identifying identity information through differences between different individuals. The use of face recognition in third-party payment platforms will greatly improve the efficiency and security of payment. Based on this, the paper studies and designs the third-party payment system for face recognition in the context of Internet artificial intelligence to improve the convenience and security of face payment.
LiY., ChenY. and WangG., Face recognition attendance system based on pca approach, Caddm26(2) (2016), 8–12.
2.
HuangS.M., ChouY.T. and YangJ.F., Low-resolution face recognition in uses of multiple-size discrete cosine transforms and selective gaussian mixture models, Computer Vision Iet8(5) (2014), 382–390.
3.
PaulA. and RhoS., Probabilistic model for M2M in IoT networking and communication, Telecommunication Systems62(1) (2016), 59–66.
4.
Thakare GirishS., PrashantDr. and DeshmukhR., Performance Analysis of Real Time Task Scheduling Algorithm, International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE)5(6), 2017.
5.
TanY., CaoF. and CaiM.C.M., A new system of face recognition: Using fuzziness and sparsity. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems23(06) (2015), 829–844.
6.
BhattacharjeeD., PaulA., KimJ.H. and KarthigaikumarP., An immersive learning model using evolutionary learning, Computers & Electrical Engineering65 (2018), pp. 236–249.
7.
HuH., Face recognition with image sets using locally grassmannian discriminant analysis, IEEE Transactions on Circuits & Systems for Video Technology24(9) (2014), 1461–1474.
8.
Shubhangi T. Raut, Dr. Abha Khandelwal and Dr. S.B. Kishor, A Survey on Literature Review of the Usability of HCI, International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE)5(7), 2017.
9.
BhattH.S., SinghR. and VatsaM., On recognizing faces in videos using clustering-based re-ranking and fusion, IEEE Transactions on Information Forensics & Security9(7) (2014), 1056–1068.
10.
SinghS., GanatraM., ShingrakhiaH., PatelZ. and MotorDC., Speed Control with PID Controller: A Review, International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE)5(5), 2017.
11.
FaragA.A., BhanuB., HancockE. and MedioniG., Guest editorial special issue on facial biometrics in the wild, Information Forensics & Security IEEE Transactions on9(12) (2017), 2019–2023.
12.
CoşkunM., Ayşegül Uçar, Özal Yildirim and Yakup Demir, Face recognition based on convolutional neural network, Modern Electrical and Energy Systems (MEES), International Conference on 2017.
13.
SamekA.S. and SheremetaR.M., Recognizing contributors: An experiment on public goods, Experimental Economics17(4) (2014), 673–690.
14.
MoonB.J., SmithJ.S., AmesC.P., ShaffreyC.I., LafageV., SchwabF., et al., Prevalence and type of cervical deformities among adults with parkinson’s disease: A cross-sectional study, J Neurosurg Spine24(4) (2016), 527–534.
