Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
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Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
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Is Internet becoming a Major Contributor for Global warming - The Online Carbon Footprint
Volume-2 | Issue-4
Augmented Reality in Education
Volume-2 | Issue-4
A Study on Various Task-Work Allocation Algorithms in Swarm Robotics
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IoT based Biotelemetry for Smart Health Care Monitoring System
Volume-2 | Issue-3
Tungsten DiSulphide FBG Sensor for Temperature Monitoring in Float Glass Manufacturing
Volume-2 | Issue-4
GUI based Industrial Monitoring and Control System
Volume-3 | Issue-2
AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1
Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1
Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3
Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3
Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2
Volume - 3 | Issue - 1 | march 2021
Published
11 May, 2021
Emotion prediction, the sub-domain of sentiment analysis helps to analyze the emotion. Recently, the prediction of children's behavior based on their present emotional activities is remaining as a challenging task. Henceforth, the deep learning algorithms are used to support and assist in the process of children's behavior prediction by considering the emotional features with a good accuracy rate. Besides, this article presents the prediction of children's behavior based on their emotion with the deep learning classifiers method. To analyze the performance, decision tree and naïve Bayes probability model are compared. Totally, 35 sample emotions are considered in the prediction process of deep learning classifier with a probability model. Furthermore, the hybrid emotions are incorporated in the proposed dataset. The comparison between both the decision tree and the Naïve Bayes method has been performed to predict the children's emotions after the classification. Based on the probability model of naïve Bayes method and decision tree, naïve Bayes method provides good results in terms of recognition rate and prediction accuracy when compared to the decision tree method. Therefore, a fusion of these two algorithms is proposed for predicting the emotions involved in children's behavior. This research article includes the combined algorithm mathematical proof of prediction based on the emotion samples. This article discusses about the future scope of the proposal and the obtained prediction results.
KeywordsDeep learning human emotion recognition
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