PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
  • Sesja wygasła!
Tytuł artykułu

REGA: Real-Time Emotion, Gender, Age Detection Using CNN - A Review

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Konferencja
International Conference on Research in Management & Technovation (05-06.12.2020 ; Nagpur, Indie)
Języki publikacji
EN
Abstrakty
EN
In this paper we describe a methodology and an algorithm to estimate the real-time age, gender, and emotion of a human by analyzing of face images on a webcam. Here we discuss the CNN based architecture to design a real-time model. Emotion, gender and age detection of facial images in webcam play an important role in many applications like forensics, security control, data analysis,video observation and human-computer interaction. In this paper we present some method \& techniques such as PCA,LBP, SVM, VIOLA-JONES, HOG which will directly or indirectly used to recognize human emotion, gender and age detection in various conditions.
Rocznik
Tom
Strony
115--118
Opis fizyczny
Bibliogr. 16 poz., rys.
Twórcy
  • Student, School of Computing Sciences(IT), The Assam Kaziranga University, Jorhat, Assam ,India
autor
  • Student, School of Computing Sciences(IT), The Assam Kaziranga University, Jorhat, Assam ,India
  • School of Computing Sciences(IT) ,The Assam Kaziranga University, Jorhat, Assam, India
Bibliografia
  • 1. Md. Jashim Uddin, Dr. Paresh Chandra Barman, Khandaker Takdir Ahmed S.M. Abdur Rahim , Abu Rumman Refat , Md Abdullah-Al- Imran6 "A Convolutional Neural Network for Real-time Face Detection and Emotion & Gender Classification" IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)
  • 2. Thakshila R. Kalansuriya and Anuja T. Dharmaratne,"Neural Network based Age and Gender Classification for Facial Images" International Journal on Advances in ICT for Emerging Regions
  • 3. M. R. Dileepa and Ajit Dantib "Human Age and Gender Prediction Based on Neural Networks and Three Sigma Control Limits" ISSN: 0883-9514 (Print) 1087- 6545 (Online) Journal homepage: http://www.tandfonline.com/loi/uaai20
  • 4. 2018-Sepidehsadat Hosseini, Seok Hee Lee, Hyuk Jin Kwon, Hyung Il Koo Nam Ik Cho, “Age and Gender Classification Using Wide Convolutional Neural Network and Gabor Filter”, IEEE2018.
  • 5. Imane Lasri, Anouar Riad Solh Mourad E Belkacemi, “Facial Emotion Recognition of Students using Convolutional Neural Network”, IEEE- 2019.
  • 6. Rajesh Kumar G A, Ravi Kant Kumar Goutam Sanyal, “Facial Emotion Analysis using Deep Convolutional Neural Network”,2017 International Conference on Signal Processing and Communication (ICSPC). http://dx.doi.org/10.1109/cspc.2017.8305872, Pg.No.- 369 to374.
  • 7. Md Abdullah-Al-Imran “A Convolutional Neural Network for Real-time Face Detection and Emotion & Gender Classification’’ e-ISSN: 2278-2834, p- ISSN: 2278-8735. Volume15, Issue 3, Ser. I (May - June2020), PP 37-46.
  • 8. S L Happy and Aurobinda Routray “Automatic Facial Expression Recognition Using Features of Salient Facial Patches’’ http://dx.doi.org/10.1109/ TAFFC. 2014. 2386334 https://rb.gy/9m5dt2.
  • 9. Ramin Azarmehr, Robert Laganiere, Won-Sook Lee Real-time Embedded Age and Gender Classification in Unconstrained Video h ttps://rb.gy/pnvd2n.
  • 10. Jang-Hee Yoo, So-Hee Park, and Yongjin Lee “Real-Time Ageand Gender Estimation from Face Image” ISBN: 978-0-6480147-3-7.
  • 11. Octavio Arriaga1 and Matias Valdenegro-Toro and Paul G. Pl¨oger Real-time Convolutional Neural Networks for emotion and gender classification.”
  • 12. Eran Eidinger, Roee Enbar, Tal Hassner “Age and Gender Estimation of Unfiltered Faces’’
  • 13. Ajit P. Gosavi, S. R. Khot “Facial Expression Recognition Using Principal Component Analysis” ISSN: 2231-2307, Volume-3, Issue-4, September 2013
  • 14. Sidharth Nair, Dipesh Nair, “Detection of Gender, Age and Emotion of a Human Image using Facial Features” e-ISSN: 2395-0056 www.irjet.netp- ISSN: 2395-0072
  • 15. Rekha N, Dr.M.Z.Kurian "Face Detection in Real Time Based on HOG" international journal of advanced Research in computer engineering & tchnology volume 3 issue 4,april2014 ISSN:2278-1323
  • 16. Tanner Gilligan, Baris Akis Emotion AI, Real-Time Emotion Detection using CNN " http://web.stanford.edu/class/cs231a/prev_projects_2016/emotion-ai-real.pdf
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-84712e83-5a0d-433d-b1c5-2c4b3fc4b92a
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.