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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM14355

Facial Expressions Detection Using CNN & RNN Algorithms

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM14355

Volume:

6 |

6 |

Jun 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM14355

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GD

G. Durvasi

NRS

N. Rohit Sai

KGP

K. GuruSai Pavan

PSD

P.Ch. Sai Deepak

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Abstract

Human Face expression Recognition is one of the most powerful and challenging tasks in social communication. Generally, face expressions are natural and direct means for human beings to communicate their emotions and intentions. Face expressions are the key characteristics of non-verbal communication. This paper describes the survey of Face Expression Recognition (FER) techniques which include the three major stages such as preprocessing, feature extraction and classification. This survey explains the various types of FER techniques with its major contributions. The performance of various FER techniques is compared based on the number of expressions recognized and complexity of algorithms. Databases like JAFFE, CK, and some other variety of facial expression databases are discussed in this survey.

KEYWORDS

Facial expression recognition Feature extraction Deep learning Convolutional neural network Recurrent neural network.

Cite This Article

G. Durvasi, N. Rohit Sai, K. GuruSai Pavan, P.Ch. Sai Deepak, "Facial Expressions Detection Using CNN & RNN Algorithms," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 6, Jun 2022. https://doi.org/10.55041/IJSREM14355

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Publication Date

6/14/2022

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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