JOURNAL ARTICLE

Facial Emotion Recognition Using Deep Neural Network

Abstract

The major part in the process of humanization of systems is the capability of distinguishing the emotions of the person. In this research paper we represent the composition of an instinctive system that is capable of detecting the emotion by using their facial expressions. Three techniques of neural network are tailored, educated and subordinated to different jobs, after this the performance of the network was improved. A live videotape operation that can currently simulate the person’s emotion depicts how well the model connects to the world. Since the invention of computers many technologists and masterminds are introducing instinctively intelligent systems that are very helpful to humans mentally and physically. In the previous decades the usage of computer has increased rapidly which helps in developing fast literacy systems, where internet has provided vast quantum of data for teaching the machine. These two enlargements elevated the exploration on intelligent learning systems by using neural networks in favorable ways. The facial emotion detection machine needs to be trained to get the system ready. The installation of OpenCV(Open Source Computer Vision) is essential for this machine. OpenCV is a library that is required for computer vision.

Keywords:
Computer science Process (computing) Artificial neural network Artificial intelligence Human–computer interaction Facial expression Emotion recognition Instinct Machine learning

Metrics

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Cited By
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FWCI (Field Weighted Citation Impact)
15
Refs
0.10
Citation Normalized Percentile
Is in top 1%
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Topics

IoT-based Smart Home Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Face and Expression Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Smart Systems and Machine Learning
Physical Sciences →  Computer Science →  Computer Networks and Communications

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