A deep learning architecture of RA-DLNet for visual sentiment analysis

Volume: 26, Issue: 4, Pages: 431 - 451
Published: May 25, 2020
Abstract
Visual media has become one of the most potent means of conveying opinions or sentiments on the web. Millions of photos are being uploaded by the people on famous social networking sites for expressing themselves. The area of visual sentiment analysis is abstract in nature due to the high level of biasing in the human recognition process. This work proposes a residual attention-based deep learning network (RA-DLNet), which examines the problem...
Paper Details
Title
A deep learning architecture of RA-DLNet for visual sentiment analysis
Published Date
May 25, 2020
Volume
26
Issue
4
Pages
431 - 451
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