Manuscript Number : CSEIT1833684
A Review of Classification Methods for Social Emotion Analysis
Authors(2) :-Selvapriya M , Dr.Maria Priscilla. G Emotion classification has a broad range of applications. There are many application which uses Facial Expression to evaluate human nature, feelings, judgment, opinion. Recognizing Human Facial Expression is not a simple task because of some circumstances due to illumination, facial occlusions, face color/shape etc. Moreover, online comments are typically characterized by a sparse feature space, which makes the corresponding emotion classification tasks are very difficult. In our research work, social emotional classifications are classified through artificial neural network (ANN), deep learning and rich hybrid neural network (HNN) which will directly and indirectly used to recognize human expression in various conditions. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. The analysed methodologies are implemented using Matlab. The experimental results show that the CNN model attained better classification accuracy compared than rich Hybrid Neural Network (HNN) and Artificial Neural Network (ANN) schemes. The performance evaluation conducted was proved that the each and every method has unique advantage and disadvantages among each other.
Selvapriya M Artificial Neural Network (ANN), Hybrid Neural Network (HNN), convolutional neural network (CNN) Publication Details Published in : Volume 3 | Issue 3 | March-April 2018 Article Preview
Research Scholar, Student Member, IEEE , Department of Computer Science, Sri Ramakrishna College of Arts and Science, Formerly S.N.R SONS College(Autonomous), Coimbatore, Tamilnadu, India
Dr.Maria Priscilla. G
Assistant Professor, Senior Member, IEEE, Head, Department of Computer Science, Sri Ramakrishna College of Arts and Science, Formerly S.N.R SONcollege(Autonomous), Coimbatore, Tamil Nadu, India
Date of Publication : 2018-04-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1737-1750
Manuscript Number : CSEIT1833684
Publisher : Technoscience Academy