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From pixels to sentiment: fine-tuning CNNs for visual sentiment prediction

Author
Campos, V.; Jou, B.; Giro, X.
Type of activity
Journal article
Journal
Image and vision computing
Date of publication
2017-02-05
Volume
65
First page
15
Last page
22
DOI
https://doi.org/10.1016/j.imavis.2017.01.011 Open in new window
Repository
http://hdl.handle.net/2117/102593 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0262885617300355 Open in new window
Abstract
Visual multimedia have become an inseparable part of our digital social lives, and they often capture moments tied with deep affections. Automated visual sentiment analysis tools can provide a means of extracting the rich feelings and latent dispositions embedded in these media. In this work, we explore how Convolutional Neural Networks (CNNs), a now de facto computational machine learning tool particularly in the area of Computer Vision, can be specifically applied to the task of visual sentime...
Citation
Campos, V., Jou, B., Giro, X. From pixels to sentiment: fine-tuning CNNs for visual sentiment prediction. "Image and vision computing", 5 Febrer 2017, vol. 65, p. 15-22.
Keywords
convolutional neural networks, fine-tuning strategies, sentiment, social multimedia
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

  • Campos Camúñez, Victor  (author)
  • Jou, Brendan  (author)
  • Giro Nieto, Xavier  (author)