|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
||||||||||||||
Issue: May 2024
Volume 9 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 96
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | FACIAL MICRO EXPRESSION, AGE AND GENDER RECOGNITION USING DEEP CONVOLUTIONAL NEURAL NETWORK |
| Authors Name: | Laxmi H , Dr. Prabha R |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_208296
|
| Published Paper Id: | IJNRD2311086 |
| Published In: | Volume 8 Issue 11, November-2023 |
| DOI: | |
| Abstract: | Identification of facial micro-expressions, emotions and these micro-expressions is a basic element of human and social interaction. Micro expressions are the result of voluntary and non-voluntary emotional reactions to stimuli that last for a few microseconds. Facial recognition and emotional identification is useful for biological medical applications such as surveillance, safety, brain monitoring of epilepsy and paralysis patients, and human computer interaction. The technology used in this paper is Convolutional Neural Networks (CNNs), which involve constructing characteristic maps using filtering data as input to do the convolution. The neural network is part of the artificial neural network, which is mainly applied to image detection and classification processes. The results obtained by testing a model composed of several input images give the output. The model recognizes the micro expressions of the face and highlights the output image. The accuracy of the group's image detection proves that the system saves time otherwise spent identifying each individual's emotions, but also have high accuracy for images of multiple people. Age assessment plays a leading role in applications such as biometric assessment, virtual makeup and virtual demonstration applications for jewelry and eyewear by mapping the face according to the found age. Lens Kart is an application that gives customers the option of trying it out. Age estimation is a subfield of facial recognition and facial tracking that in combination can predict individual health. Many medical applications use this mechanism to monitor their daily activities to keep track of their health. China uses this face detection technique for the identification of service drivers and the identification of Jaywalker. A number of essential machine learning algorithms to predict age and gender have been used. CNN methods are used to find an age and gender identification. In this implementation, Open CV and CNN has been used to predict the age and gender of a given person. |
| Keywords: | Deep Learning, Image segmentation, Edge Detection, Neural Networks, face features, Convolutional Neural Network. |
| Cite Article: | "FACIAL MICRO EXPRESSION, AGE AND GENDER RECOGNITION USING DEEP CONVOLUTIONAL NEURAL NETWORK", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.a789-a795, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311086.pdf |
| Downloads: | 000118760 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2311086 Registration ID: 208296 Published In: Volume 8 Issue 11, November-2023 DOI (Digital Object Identifier): Page No: a789-a795 Country: Bangalore, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2311086 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2311086 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn