A Multimodal Tensor-Based Late Fusion Approach for Satellite Image Search in Sentinel 2 Images

Gialampoukidis, Ilias; Moumtzidou, Anastasia; Bakratsas, Marios; Vrochidis, Stefanos; Kompatsiaris, Ioannis

doi:10.1007/978-3-030-67835-7_25

Cited by 4 publications

(1 citation statement)

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“…urban area, rock, water, snow, etc.). These concepts also appear in social media streams, where a concept extraction algorithm is applied, and allow for semantically correlating social media posts or events with satellite images that contain the same concepts in their patches [6].…”

Section: Data Mining In Social Mediamentioning

confidence: 99%

Multimodal Data Fusion of Social Media and Satellite Images for Emergency Response and Decision-Making

Gialampoukidis

Andreadis

Vrochidis

et al. 2021

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS

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Artificial Intelligence (AI) is already part of our lives and is extensively entering the space sector to offer value-added Earth Observation (EO) products and services. The Copernicus programme provides data on a free, full and open basis, while the recently launched Data and Information Access Service (DIAS) providers index, store and exchange tremendous amounts of data and cloud infrastructure computational resources. Copernicus data and other georeferenced data sources are often highly heterogeneous, distributed and semantically fragmented. One example is the massively generated social media data from citizen observations, including visual, textual and spatiotemporal information. Social media information offers reliable, timely and very prescriptive information about a crisis event. In this work we present the multimodal fusion aspects for combining satellite images and social media for emergency response, such as flood monitoring and extreme weather conditions in polar regions.

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Section: Data Mining In Social Mediamentioning

confidence: 99%