Facial emotion recognition using convolutional neural networks
- Title
- Facial emotion recognition using convolutional neural networks
- Creator
- Sarvakar K.; Senkamalavalli R.; Raghavendra S.; Santosh Kumar J.; Manjunath R.; Jaiswal S.
- Description
- Emotional expressivity has always been a simple job for people, but computer programming is much harder to accomplish. Image emotions may be recognised by recent developments in computer vision and machine learning. In this article, we present a new method to detect face emotion. Use neural networks convolutionary (FERC). The FERC is based on a CNN network of two parts: the first portion removed the backdrop of the image, the second part removed the face vector. The expressional vector (EV) is utilised in the FERC model to detect the fve different kinds of regular facial expressions. The double-level CNN is continuous and the weights and exponent values of the final perception layer vary with each iteration. In that it improves accuracy, FERC varies from widely utilised CNN single-level technology. Moreover, EV generation prevents the development of a number of issues before a new background removal process is used (for example distance from the camera). 2021
- Source
- Materials Today: Proceedings, Vol-80, pp. 3560-3564.
- Date
- 2023-01-01
- Publisher
- Elsevier Ltd
- Subject
- CNN; Emotion recognition; Facial expression
- Coverage
- Sarvakar K., Information Technology Department, U.V. Patel College of Engineering, Ganpat University, Gujarat, Mehsana, 384012, India; Senkamalavalli R., CSE Department, East Point College of Engineering, Bangalore, India; Raghavendra S., Department of Computer Science and Engineering, School of Engineering and Technology, Christ Deemed to be University, Bengaluru, 560074, India; Santosh Kumar J., Department of Computer Science and Engineering, K S School of Engineering and Management, Bengaluru, 56019, India; Manjunath R., Department of Computer Science and Engineering, R R Institute of Technology, Bengaluru, 560090, India; Jaiswal S., Department of Computer Science & Information Technology (CSIT), Guru Ghasidas Vishwavidyalaya, (A Central University)Koni, (C.G.), Bilaspur, 495009, India
- Rights
- Restricted Access
- Relation
- ISSN: 22147853
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Sarvakar K.; Senkamalavalli R.; Raghavendra S.; Santosh Kumar J.; Manjunath R.; Jaiswal S., “Facial emotion recognition using convolutional neural networks,” CHRIST (Deemed To Be University) Institutional Repository, accessed April 20, 2025, https://archives.christuniversity.in/items/show/14770.