Loading…
A Comprehensive Survey of Face Recognition Advancements
Face recognition technology has experienced significant advancements in recent years due to the rapid progress in deep learning techniques. The purpose of this comprehensive literature review is to examine the various applications and underlying methodologies of face recognition. With recent advance...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference Proceeding |
| Language: | English |
| Subjects: | |
| Online Access: | Request full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | |
| container_end_page | 5 |
| container_issue | |
| container_start_page | 1 |
| container_title | |
| container_volume | |
| creator | Mane, Sunil B. Shah, Nisarg Garje, Vaibhav Tejwani, Aman |
| description | Face recognition technology has experienced significant advancements in recent years due to the rapid progress in deep learning techniques. The purpose of this comprehensive literature review is to examine the various applications and underlying methodologies of face recognition. With recent advancements in face recognition techniques, a wider range of scenarios and challenges can be addressed. In this survey, we explore the latest developments in face recognition, including pitch variations, lighting changes, occlusions, and varied environments. The survey provides a comprehensive review of face recognition technology, covering applications, methodologies, dataset usage, model accuracy, and workings. Additionally, it analyzes three main approaches to face recognition for static images: traditional (or classical), deep learning-based, and hybrid. Hence, providing an overview of and comparing some of the popular face recognition approaches and techniques is the main objective of this paper. |
| doi_str_mv | 10.1109/ICCUBEA61740.2024.10774962 |
| format | conference_proceeding |
| fullrecord | <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_10774962</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10774962</ieee_id><sourcerecordid>10774962</sourcerecordid><originalsourceid>FETCH-ieee_primary_107749623</originalsourceid><addsrcrecordid>eNqFzr0OgjAUQOFqYiJR3sChcQdvW-DSEYlGV39mQ_CqNVIIRRLe3kVnpzN8y2FsKSAUAvRqn-fn9SZLBEYQSpBRKAAx0okcMV-jTlUMSgtEGDNPIopAqDidMt-5JwAoCREksccw43ldNS09yDrTEz--254GXt_4tiiJH6is79Z0prY8u_aFLaki27k5m9yKlyP_2xlbbDenfBcYIro0ramKdrj8ntQf_gB52Doz</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A Comprehensive Survey of Face Recognition Advancements</title><source>IEEE Xplore All Conference Series</source><creator>Mane, Sunil B. ; Shah, Nisarg ; Garje, Vaibhav ; Tejwani, Aman</creator><creatorcontrib>Mane, Sunil B. ; Shah, Nisarg ; Garje, Vaibhav ; Tejwani, Aman</creatorcontrib><description>Face recognition technology has experienced significant advancements in recent years due to the rapid progress in deep learning techniques. The purpose of this comprehensive literature review is to examine the various applications and underlying methodologies of face recognition. With recent advancements in face recognition techniques, a wider range of scenarios and challenges can be addressed. In this survey, we explore the latest developments in face recognition, including pitch variations, lighting changes, occlusions, and varied environments. The survey provides a comprehensive review of face recognition technology, covering applications, methodologies, dataset usage, model accuracy, and workings. Additionally, it analyzes three main approaches to face recognition for static images: traditional (or classical), deep learning-based, and hybrid. Hence, providing an overview of and comparing some of the popular face recognition approaches and techniques is the main objective of this paper.</description><identifier>EISSN: 2771-1358</identifier><identifier>EISBN: 9798350391770</identifier><identifier>DOI: 10.1109/ICCUBEA61740.2024.10774962</identifier><language>eng</language><publisher>IEEE</publisher><subject>Accuracy ; Computational modeling ; Convolutional neural networks ; Deep learning ; Deep learning techniques ; Face recognition ; Face recognition technology ; holistic ; Lighting ; pitch variations ; Representation learning ; Reviews ; Surveys ; Synthetic data</subject><ispartof>International Conference on Computing Communication Control and Automation (Online), 2024, p.1-5</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10774962$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10774962$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Mane, Sunil B.</creatorcontrib><creatorcontrib>Shah, Nisarg</creatorcontrib><creatorcontrib>Garje, Vaibhav</creatorcontrib><creatorcontrib>Tejwani, Aman</creatorcontrib><title>A Comprehensive Survey of Face Recognition Advancements</title><title>International Conference on Computing Communication Control and Automation (Online)</title><addtitle>ICCUBEA</addtitle><description>Face recognition technology has experienced significant advancements in recent years due to the rapid progress in deep learning techniques. The purpose of this comprehensive literature review is to examine the various applications and underlying methodologies of face recognition. With recent advancements in face recognition techniques, a wider range of scenarios and challenges can be addressed. In this survey, we explore the latest developments in face recognition, including pitch variations, lighting changes, occlusions, and varied environments. The survey provides a comprehensive review of face recognition technology, covering applications, methodologies, dataset usage, model accuracy, and workings. Additionally, it analyzes three main approaches to face recognition for static images: traditional (or classical), deep learning-based, and hybrid. Hence, providing an overview of and comparing some of the popular face recognition approaches and techniques is the main objective of this paper.</description><subject>Accuracy</subject><subject>Computational modeling</subject><subject>Convolutional neural networks</subject><subject>Deep learning</subject><subject>Deep learning techniques</subject><subject>Face recognition</subject><subject>Face recognition technology</subject><subject>holistic</subject><subject>Lighting</subject><subject>pitch variations</subject><subject>Representation learning</subject><subject>Reviews</subject><subject>Surveys</subject><subject>Synthetic data</subject><issn>2771-1358</issn><isbn>9798350391770</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNqFzr0OgjAUQOFqYiJR3sChcQdvW-DSEYlGV39mQ_CqNVIIRRLe3kVnpzN8y2FsKSAUAvRqn-fn9SZLBEYQSpBRKAAx0okcMV-jTlUMSgtEGDNPIopAqDidMt-5JwAoCREksccw43ldNS09yDrTEz--254GXt_4tiiJH6is79Z0prY8u_aFLaki27k5m9yKlyP_2xlbbDenfBcYIro0ramKdrj8ntQf_gB52Doz</recordid><startdate>20240823</startdate><enddate>20240823</enddate><creator>Mane, Sunil B.</creator><creator>Shah, Nisarg</creator><creator>Garje, Vaibhav</creator><creator>Tejwani, Aman</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20240823</creationdate><title>A Comprehensive Survey of Face Recognition Advancements</title><author>Mane, Sunil B. ; Shah, Nisarg ; Garje, Vaibhav ; Tejwani, Aman</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_107749623</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accuracy</topic><topic>Computational modeling</topic><topic>Convolutional neural networks</topic><topic>Deep learning</topic><topic>Deep learning techniques</topic><topic>Face recognition</topic><topic>Face recognition technology</topic><topic>holistic</topic><topic>Lighting</topic><topic>pitch variations</topic><topic>Representation learning</topic><topic>Reviews</topic><topic>Surveys</topic><topic>Synthetic data</topic><toplevel>online_resources</toplevel><creatorcontrib>Mane, Sunil B.</creatorcontrib><creatorcontrib>Shah, Nisarg</creatorcontrib><creatorcontrib>Garje, Vaibhav</creatorcontrib><creatorcontrib>Tejwani, Aman</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Mane, Sunil B.</au><au>Shah, Nisarg</au><au>Garje, Vaibhav</au><au>Tejwani, Aman</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Comprehensive Survey of Face Recognition Advancements</atitle><btitle>International Conference on Computing Communication Control and Automation (Online)</btitle><stitle>ICCUBEA</stitle><date>2024-08-23</date><risdate>2024</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><eissn>2771-1358</eissn><eisbn>9798350391770</eisbn><abstract>Face recognition technology has experienced significant advancements in recent years due to the rapid progress in deep learning techniques. The purpose of this comprehensive literature review is to examine the various applications and underlying methodologies of face recognition. With recent advancements in face recognition techniques, a wider range of scenarios and challenges can be addressed. In this survey, we explore the latest developments in face recognition, including pitch variations, lighting changes, occlusions, and varied environments. The survey provides a comprehensive review of face recognition technology, covering applications, methodologies, dataset usage, model accuracy, and workings. Additionally, it analyzes three main approaches to face recognition for static images: traditional (or classical), deep learning-based, and hybrid. Hence, providing an overview of and comparing some of the popular face recognition approaches and techniques is the main objective of this paper.</abstract><pub>IEEE</pub><doi>10.1109/ICCUBEA61740.2024.10774962</doi></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | EISSN: 2771-1358 |
| ispartof | International Conference on Computing Communication Control and Automation (Online), 2024, p.1-5 |
| issn | 2771-1358 |
| language | eng |
| recordid | cdi_ieee_primary_10774962 |
| source | IEEE Xplore All Conference Series |
| subjects | Accuracy Computational modeling Convolutional neural networks Deep learning Deep learning techniques Face recognition Face recognition technology holistic Lighting pitch variations Representation learning Reviews Surveys Synthetic data |
| title | A Comprehensive Survey of Face Recognition Advancements |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T07%3A21%3A29IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=A%20Comprehensive%20Survey%20of%20Face%20Recognition%20Advancements&rft.btitle=International%20Conference%20on%20Computing%20Communication%20Control%20and%20Automation%20(Online)&rft.au=Mane,%20Sunil%20B.&rft.date=2024-08-23&rft.spage=1&rft.epage=5&rft.pages=1-5&rft.eissn=2771-1358&rft_id=info:doi/10.1109/ICCUBEA61740.2024.10774962&rft.eisbn=9798350391770&rft_dat=%3Cieee_CHZPO%3E10774962%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-ieee_primary_107749623%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=10774962&rfr_iscdi=true |