Real Time Automatic Attendance System for Face Recognition Using Face API and OpenCV

Khan, Sikandar Zulqarnain; Akram, Adeel; Usman, Nighat

doi:10.1007/s11277-020-07224-2

Cited by 62 publications

(18 citation statements)

References 7 publications

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“…e basic architecture is shown in Figure 1. e education platform provides basic information services, covering resources, curriculum design, evaluation system, and learning modules [12]. e network server is used to realize the construction of LAN.…”

Section: Smart Classroom Teaching Platform Architecturementioning

confidence: 99%

Application of Internet of Things Architecture in Intelligent Classroom Teaching Analysis in Colleges and Universities

2022

Mobile Information Systems

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Smart classroom is based on information technology, and its operation, upgrading, and development need technical support. At present, most of the smart classroom teaching adopts traditional architecture, highlighting the characteristics of disciplines, insufficient data processing, and narrow application fields. Based on this, this paper studies and analyzes the application of Internet of things architecture in college smart classroom teaching analysis. Based on the simple analysis of the development of intelligent algorithms and smart classrooms of the Internet of things, this paper constructs a smart classroom system based on the architecture of the Internet of things, transfers it to information-based teaching, introduces an intelligent service platform, and uses intelligent algorithms to mine and cluster data. The core algorithm is improved based on K-means algorithm and grid algorithm to improve the pertinence and effectiveness of the algorithm. Through the simulation results, the improved clustering analysis algorithm can shorten the running time and improve the clustering effect. At the same time, the application test results of the algorithm also show the superiority of the clustering results, which can provide more strategies for later teaching.

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Section: Smart Classroom Teaching Platform Architecturementioning

confidence: 99%

Application of Internet of Things Architecture in Intelligent Classroom Teaching Analysis in Colleges and Universities

2022

Mobile Information Systems

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“…Then the accuracy of verification is 91.12% using the ACNN-Res50 and 98.42% using the ACNN-Res101. Khan et al discussed making a student attendance recording system using face recognition [58]. The proposed system is expected to replace the manual and biometric attendance system, which takes a long time to record attendance.…”

Section: Kamencay Et Al Compared the Of Cnn With Principal Component ...mentioning

confidence: 99%

A Survey of Face Recognition based on Convolutional Neural Network

Saragih

2022

Indonesian J. of Inf. Syst.

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Face recognition is one of the interesting research topics in the field of computer vision. In recent years, deep learning methods, especially the Convolutional Neural Network, have progressed. One of the successes of CNN is in face recognition. Face recognition by computer is a technique done so that the computer can automatically recognize faces in an image. Various researchers have conducted related research on facial recognition. This survey presents researches related to face recognition based on Convolutional Neural Network that has been conducted. The studies used are studies that have been published in the last five years. It was performed to determine the renewal that emerged in face recognition based on Convolutional Neural Network. The basic theory of the Convolutional Neural Network, face recognition, and description of the database used in various researches are also discussed. Hopefully, this survey can provide additional knowledge regarding face recognition based on the Convolutional Neural Network.

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“…To analyze one's face and emotions automatically, emerging image processing technologies can be used. Especially, in recent years, owing to powerful machine learning technologies, various companies have provided cognitive application programing interfaces (API) for face [8,9], which automatically recognize and analyze faces within a given picture. These APIs produce values of typical emotions such as happiness and sadness, which would be helpful for the evaluation of the care effect.…”

Section: Introductionmentioning

confidence: 99%

Toward Capturing Scientific Evidence in Elderly Care: Efficient Extraction of Changing Facial Feature Points

Hirayama

Chen

Saiki

et al. 2021

Sensors

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To capture scientific evidence in elderly care, a user-defined facial expression sensing service was proposed in our previous study. Since the time-series data of feature values have been growing at a high rate as the measurement time increases, it may be difficult to find points of interest, especially for detecting changes from the elderly facial expression, such as many elderly people can only be shown in a micro facial expression due to facial wrinkles and aging. The purpose of this paper is to implement a method to efficiently find points of interest (PoI) from the facial feature time-series data of the elderly. In the proposed method, the concept of changing point detection into the analysis of feature values is incorporated by us, to automatically detect big fluctuations or changes in the trend in feature values and detect the moment when the subject’s facial expression changed significantly. Our key idea is to introduce the novel concept of composite feature value to achieve higher accuracy and apply change-point detection to it as well as to single feature values. Furthermore, the PoI finding results from the facial feature time-series data of young volunteers and the elderly are analyzed and evaluated. By the experiments, it is found that the proposed method is able to capture the moment of large facial movements even for people with micro facial expressions and obtain information that can be used as a clue to investigate their response to care.

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Real Time Automatic Attendance System for Face Recognition Using Face API and OpenCV

Cited by 62 publications

References 7 publications

Application of Internet of Things Architecture in Intelligent Classroom Teaching Analysis in Colleges and Universities

Application of Internet of Things Architecture in Intelligent Classroom Teaching Analysis in Colleges and Universities

A Survey of Face Recognition based on Convolutional Neural Network

Toward Capturing Scientific Evidence in Elderly Care: Efficient Extraction of Changing Facial Feature Points

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