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20162023
most citedDeriving Emotions and Sentiments from Visual Content: A Disaster Analysis Use Case

5 citations · 20 across the 13 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV2019

Sentiment Analysis from Images of Natural Disasters

Syed Zohaib, Kashif Ahmad, Nicola Conci +1

Social media have been widely exploited to detect and gather relevant information about opinions and events. However, the relevance of the information is very subjective and rather…

cs.CV2019★ 4 cited

Multi-Modal Machine Learning for Flood Detection in News, Social Media and Satellite Sequences

Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah +4

In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Soci…

cs.CV2019★ 2 cited

Active Learning for Event Detection in Support of Disaster Analysis Applications

Naina Said, Kashif Ahmad, Nicola Conci +1

Disaster analysis in social media content is one of the interesting research domains having abundance of data. However, there is a lack of labeled data that can be used to train ma…

cs.IR2019

Natural Disasters Detection in Social Media and Satellite imagery: a survey

Naina Said, Kashif Ahmad, Michael Regular +4

The analysis of natural disaster-related multimedia content got great attention in recent years. Being one of the most important sources of information, social media have been craw…

cs.IR2019

Automatic detection of passable roads after floods in remote sensed and social media data

Kashif Ahmad, Konstantin Pogorelov, Michael Riegler +4

This paper addresses the problem of floods classification and floods aftermath detection utilizing both social media and satellite imagery. Automatic detection of disasters such as…