Face Recognition Using Machine Learning Models - Comparative Analysis and impact of dimensionality reduction

Yaswanthram, P.; Sabarish, B. A.

doi:10.1109/icaecc54045.2022.9716590

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2024

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Cited by 8 publications

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“…H. Aung et al [2] The paper presents a methodology that uses the YOLO algorithm and the VGG16 convolutional neural network to identify face blends in live video. The VGG16 grid is used for extraction, and the YOLO.V2 environment is adjusted for visibility.…”

Section: Objective Of the Studymentioning

confidence: 99%

Surveillance System with Impediment of Face Discovery Using Python

Mandal,

Sharma

2024

Adhyayan J.

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In recent years, It is an active area of research and development with there ongoing and active work on computer vision. This paper presents an empirical literature review of the existing research on human facial recognition as up-to-date. This research start providing the reader with a brief on the uses and working of face recognition. The most recent approaches to facial recognition are then reviewed in the literature. The performance and drawbacks of these face recognition algorithms are also tested through use of the Labelled Wild Face (LWF) face dataset images as well as real time images. With the increasing use of real-time facial recognition systems, it is important to examine the accuracy of these systems given the reliability and 94.23% accuracy are achieved for facial recognition by the proposed model.

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Section: Objective Of the Studymentioning

confidence: 99%