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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Detection of Visual Positive Sentiment using PCNN
Digital Object Identifier (DOI) : 10.14569/IJACSA.2019.0100134
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 1, 2019.
Abstract: Many people all over the world use online social networks to express their feeling and sharing their experience, and the easiest way from their perspective is using images and videos to do so. This paper shows the utilization of two techniques (Viola et al algorithm and Pulse coupled Neural Network) in visual sentiment analysis using a hand-labeled dataset. The proposed system, which uses the PCNN with NN classifier, achieves 96% right classification, whereas Viola algorithm achieves 94% for the same dataset.
Keywords: Visual sentiment analysis; pulse coupled neural network (PCNN); viola et al. algorithm
Samar H. Ahmed, Emad Nabil and Amr A. Badr, “Detection of Visual Positive Sentiment using PCNN” International Journal of Advanced Computer Science and Applications(IJACSA), 10(1), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100134
@article{Ahmed2019,
title = {Detection of Visual Positive Sentiment using PCNN},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100134},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100134},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {1},
author = {Samar H. Ahmed and Emad Nabil and Amr A. Badr}
}
