Situation awareness in ai-based technologies and multimodal systems: Architectures, challenges and applications
Situation Awareness (SA) is a process of sensing, understanding and predicting the
environment and is an important component in complex systems. The reception of …
environment and is an important component in complex systems. The reception of …
Memory-aware continual learning with multi-modal social media streams for unsupervised disaster classification
Social media has emerged as a major hub for information dissemination during disasters. It
serves as a central repository for massive real-time updates about disasters, facilitating the …
serves as a central repository for massive real-time updates about disasters, facilitating the …
Multimodal semi-supervised learning for disaster tweet classification
During natural disasters, people often use social media platforms, such as Twitter, to post
information about casualties and damage produced by disasters. This information can help …
information about casualties and damage produced by disasters. This information can help …
Understanding image-text relations and news values for multimodal news analysis
The analysis of news dissemination is of utmost importance since the credibility of
information and the identification of disinformation and misinformation affect society as a …
information and the identification of disinformation and misinformation affect society as a …
Crisisvit: A robust vision transformer for crisis image classification
In times of emergency, crisis response agencies need to quickly and accurately assess the
situation on the ground in order to deploy relevant services and resources. However …
situation on the ground in order to deploy relevant services and resources. However …
Infrastructure ombudsman: Mining future failure concerns from structural disaster response
Current research concentrates on studying discussions on social media related to structural
failures to improve disaster response strategies. However, detecting social web posts …
failures to improve disaster response strategies. However, detecting social web posts …
Images Connect Us Together: Navigating a COVID-19 Local Outbreak in China Through Social Media Images
Social media images, curated or casual, have become a crucial component of
communicating situational information and emotions during health crises. Despite its …
communicating situational information and emotions during health crises. Despite its …
C-CLIP: Contrastive Image-Text Encoders to Close the Descriptive-Commentative Gap
W Theisen, WJ Scheirer - Proceedings of the IEEE/CVF …, 2024 - openaccess.thecvf.com
The interplay between the image and comment on a social media post is one of high
importance for understanding its overall message. Recent strides in multimodal embedding …
importance for understanding its overall message. Recent strides in multimodal embedding …
Contrastive Learning for Multimodal Classification of Crisis related Tweets
Multimodal tasks require learning a joint representation of the constituent modalities of data.
Contrastive learning learns a joint representation by using a contrastive loss. For example …
Contrastive learning learns a joint representation by using a contrastive loss. For example …
Unsupervised multimodal learning for image-text relation classification in tweets
Recent studies show that the use of multimodality can effectively enhance the understanding
of social media content. The relations between texts and images become an important basis …
of social media content. The relations between texts and images become an important basis …