Volume 31, Issue 3 (IJIEPR 2020)                   IJIEPR 2020, 31(3): 351-360 | Back to browse issues page

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Desai N, Venkatramana S, Sekhar B. Automatic Visual Sentiment Analysis with Convolution Neural network. IJIEPR 2020; 31 (3) :351-360
URL: http://ijiepr.iust.ac.ir/article-1-1070-en.html
Automatic Visual Sentiment Analysis with Convolution Neural network
N. Desai 1, S. Venkatramana2 , B.V.D.S. Sekhar3
1- N.Desai, Department of IT, SRKREC, Bhimavaram, A.P, India, , desai@srkrec.ac.in
2- 2. B.V.D.S.Sekhar, Department of IT, SRKREC, Bhimavaram, A.P, India.
3- 3. S.Venkatramana, Department of IT, SRKREC, Bhimavaram, A.P, India.
Abstract:   (3518 Views)
Today's digital world demands about automated sentiment analysis on visual and text content to significantly displaying people's feelings, opinions and emotions through text, images and videos across popular social networks. Earlier visual sentimental analysis faces many drawbacks like achieve low accuracy and more difficult to understand people opinions due to traditional techniques. Also, another major challenge is a huge number of images generated and uploaded every day across the world. This paper overcomes problems of visual sentiment analysis with the help of deep learning convolution neural network (CNN) and Affective Regions approach to achieve more meaningful sentiment reports with huge accuracy.
Keywords: Affective region, convolution neural networks, sentiment classification, visual sentiment analysis
Full-Text [PDF 711 kb]   (1398 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2020/05/3 | Accepted: 2020/05/3 | Published: 2020/05/3
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