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Human Sentiment and Activity Recognition in Disaster Situations Using Social Media Images Based on Deep Learning
2020
Sensors
A rapidly increasing growth of social networks and the propensity of users to communicate their physical activities, thoughts, expressions, and viewpoints in text, visual, and audio material have opened up new possibilities and opportunities in sentiment and activity analysis. Although sentiment and activity analysis of text streams has been extensively studied in the literature, it is relatively recent yet challenging to evaluate sentiment and physical activities together from visuals such as
doi:10.3390/s20247115
pmid:33322465
pmcid:PMC7763261
fatcat:367dozllmzh5zchqvp3h4nadym