Gaussian Mixture Models for Human Face Recognition under Illumination Variations

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Applied Mathematics

ISSN Print: 2152-7385
ISSN Online: 2152-7393
www.scirp.org/journal/am
E-mail: am@scirp.org

Google-based Impact Factor: 0.58
Citations h5-index & Ranking*

Journals Menu

"Gaussian Mixture Models for Human Face Recognition under Illumination Variations"
written by Sinjini Mitra,
published by Applied Mathematics, Vol.3 No.12A, 2012

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Artificial Emotional Intelligence: Conventional and Deep learning Approach
	Expert Systems with Applications, 2022

[2]	A scanner smartly
	2021

[3]	Advanced Face Recognition System for Real Time Applications
	2020

[4]	Extraction et fusion de points d'intérêt et textures spectraux pour l'identification, le contrôle et la sécurité
	2018

[5]	Gaussian Mixture Model and Its Applications in Semantic Image Analysis
	2018

[6]	Pendeteksian dan Pengenalan Wajah Manusia untuk Peningkatan Kinerja Kamera Pengaman
	2018

[7]	Hotel Kapsul di Jepang
	2018

[8]	Gaussian Mixture Model and Its Applications in Semantic Image Analysis.
	2018

[9]	Face characteristic detection system using ontology and supervised learning
	Int J Comput Internet Manag, 2017

[10]	Surpervised Segmentation Algorithm Based on GMM with Spatial Relationship for High Resolution Ranchromatic Remote Sensing Image
	电子与信息学报, 2017

[11]	Face Recognition System Using: LDA and GMM based Approach
	International Journal of Computer Applications, 2017

[12]	A Face Characteristic Detection System Using Ontology and Supervised Learning
	International Journal of the Computer, the Internet and Management, 2017

[13]	An Effective Modeling for Face Recognition System: LDA and GMM based Approach
	2017

[14]	融入空间关系的 GMM 全色高分辨率遥感影像监督分割方法
	2017

[15]	Missing data reconstruction using Gaussian mixture models for fingerprint images
	2016

[16]	Comparison Study of Gaussian Mixture Models for Fingerprint Image Duplication with a New Model
	Electronic Imaging, 2016

[17]	A Multi-modal Biometric System for Selective Access Control
	2016

[18]	A Novel Maximum Entropy Markov Model for Human Facial Expression Recognition
	PLOS ONE, 2016

[19]	An Investigation of fSVD and Ridgelet Transform for Illumination and Expression Invariant Face Recognition
	Advances in Intelligent Informatics, 2015

[20]	Addressing the illumination challenge in two-dimensional face recognition: a survey
	IET Computer Vision, 2015

[21]	Addressing the illumination challenge in two‐dimensional face recognition: a survey
	2015

[1]	Artificial Emotional Intelligence: Conventional and deep learning approach Expert Systems with Applications, 2023 DOI:10.1016/j.eswa.2022.118651

[2]	Artificial Emotional Intelligence: Conventional and deep learning approach Expert Systems with Applications, 2023 DOI:10.1016/j.eswa.2022.118651

[3]	Artificial Emotional Intelligence: Conventional and deep learning approach Expert Systems with Applications, 2023 DOI:10.1016/j.eswa.2022.118651

[4]	A scanner smartly Significance, 2021 DOI:10.1111/1740-9713.01526

[5]	A Novel Maximum Entropy Markov Model for Human Facial Expression Recognition PLOS ONE, 2016 DOI:10.1371/journal.pone.0162702

[6]	Missing data reconstruction using Gaussian mixture models for fingerprint images Mobile Multimedia/Image Processing, Security, and Applications 2016, 2016 DOI:10.1117/12.2224381

[7]	Advances in Intelligent Informatics Advances in Intelligent Systems and Computing, 2015 DOI:10.1007/978-3-319-11218-3_4

[8]	Addressing the illumination challenge in two-dimensional face recognition: a survey IET Computer Vision, 2015 DOI:10.1049/iet-cvi.2014.0086

[9]	Addressing the illumination challenge in two‐dimensional face recognition: a survey IET Computer Vision, 2015 DOI:10.1049/iet-cvi.2014.0086

[10]	Advances in Intelligent Informatics Advances in Intelligent Systems and Computing, 2015 DOI:10.1007/978-3-319-11218-3_4

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Applied Mathematics

Applied Mathematics

Journals Menu

Home

About SCIRP

Service

Policies