Facial Authentication System by Combining of Feature Extraction using Raspberry Pi

Gabriel, J. Zahariya; Kabilan, R.; Devaraj, G. Prince; Muthuraman, U.

doi:10.1109/icicv50876.2021.9388396

Cited by 11 publications

(2 citation statements)

References 3 publications

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“…In Ref. [11], the mixture of two main component analyses such as Principle Component Analysis (PCA) and Linear Discrimination Analysis (LDA) feature extraction are used. This method uses Euclidean distance classifications for upgrade the efficiency on face-based real-time authentication method.…”

Section: Related Workmentioning

confidence: 99%

A Novel Approach for Human Face Extraction and Detection using SAE-AFB-RFCN Framework

Jayabharathi Ponnurathinam,

Sripriya Pradabadattan

2023

ARASET

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Research into Facial Recognition Technology (FRT), which uses a person's face to identify them, has become a hot topic among scientists. Face recognition relies heavily on feature extraction and classifiers. Occlusion, illuminations, and a complicated background provide the most difficult problems for face recognition systems to overcome. With the advent of Artificial Intelligence and Deep Learning techniques now it became easy to identify different features of an Image and to detect a face. In this paper, Stacked Auto Encoder (SAE), Artificial Feeding Bird (AFB), Region Based Fully Convolutional Network (RFCN), novel approach is developed for human face feature extraction and detection. Initially, the dataset is normalized using rescaling method. Then the Stacked Auto Encoder with Artificial Feeding Birds (SAE-AFB) optimization algorithm is used for facial feature extraction and Region based Fully Convolutional Networks (R-FCN) algorithm is used for detection and classification. The WIDER Face dataset is used for training and testing. Experimental results demonstrate that the proposed SAE-AFB-RFCN framework outperforms the existing algorithms in terms of accuracy, precision, recall and F1-score.

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Section: Related Workmentioning

confidence: 99%

A Novel Approach for Human Face Extraction and Detection using SAE-AFB-RFCN Framework

Jayabharathi Ponnurathinam,

Sripriya Pradabadattan

2023

ARASET

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“…This article proposes a novel network topology that is generic and applicable to household appliances, including white goods and audiovisual and communications systems, and therefore is capable of executing real-time monitoring of their energy consumption, given this same energy waste issue in modern households and the resulting need for optimal energy use [24][25]. The proposed architecture, which uses cutting-edge information and communications technologies, enables the creation of energy-saving application domains that undertake three primary components: real-time estimation of home environment energy consumption without the use of smart metering devices; regulation of domestic appliance energy use so that home environment energy consumption stays within user-defined limits; and fully independent assessment and treatment of standby decommissioning devices [8][9][10][11].…”

Section: A Enabling Applicability Of Energy Saving Applications On Ap...mentioning

confidence: 99%

A Consumer Application with An Integrated Real-Time Power Theft Detection And Management System

Ravi¹,

Pasunkili²,

Kabilan³

et al. 2022

Proceedings of the International Conference on Intelligent Technologies in Security and Privacy for Wireless Communication, ITS

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Billing by a human operator is exposed to errors due to reading errors since the house's electric power is occasionally positioned in an inaccessible area. The notion of dynamic priority assignment to interruptions is presented, which decreases the delay time for less priority tasks that may become higher priority under certain situations. Interrupt time slicing is also being explored, which can help increase performance. The highest priority activities are completed more frequently and in a shorter amount of time. As a result, it does not need to wait for the slack time of other interrupted with greater priority. If the grid's power is reduced, the power will be maintained and controlled. When low-power generation occurs, our suggested system instantly switches to power management. When there is low power generation, all of the devices are managed based on a priority system and a timing system.

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Safe and Secure Systems in the Residence and Lender using Voice Recognition and GSM

Mary¹,

Mabel

Sam³

2022

2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC)

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Facial Authentication System by Combining of Feature Extraction using Raspberry Pi

Cited by 11 publications

References 3 publications

A Novel Approach for Human Face Extraction and Detection using SAE-AFB-RFCN Framework

A Novel Approach for Human Face Extraction and Detection using SAE-AFB-RFCN Framework

A Consumer Application with An Integrated Real-Time Power Theft Detection And Management System

Safe and Secure Systems in the Residence and Lender using Voice Recognition and GSM

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