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{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,13]],"date-time":"2024-10-13T08:40:32Z","timestamp":1728808832493},"reference-count":50,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,28]],"date-time":"2023-01-28T00:00:00Z","timestamp":1674864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"In recent years, social platforms have become integrated in a variety of economic, political and cultural domains. Social media have become the primary outlets for many citizens to consume news and information, and, at the same time, to produce and share online a large amount of data and meta-data. This paper presents an innovative system able to analyze visual information shared by citizens on social media during extreme events for contributing to the situational awareness and supporting people in charge of coordinating the emergency management. The system analyzes all posts containing images shared by users by taking into account: (a) the event class and (b) the GPS coordinates of the geographical area affected by the event. Then, a Single Shot Multibox Detector (SSD) network is applied to select only the posted images correctly related to the event class and an advanced image processing procedure is used to verify if these images are correlated with the geographical area where the emergency event is ongoing. Several experiments have been carried out to evaluate the performance of the proposed system in the context of different emergency situations caused by earthquakes, floods and terrorist attacks.<\/jats:p>","DOI":"10.3390\/info14020078","type":"journal-article","created":{"date-parts":[[2023,1,30]],"date-time":"2023-01-30T15:19:28Z","timestamp":1675091968000},"page":"78","source":"Crossref","is-referenced-by-count":1,"title":["Automatic Identification and Geo-Validation of Event-Related Images for Emergency Management"],"prefix":"10.3390","volume":"14","author":[{"given":"Marco","family":"Vernier","sequence":"first","affiliation":[{"name":"Department of Mathematics, Computer Science and Physics, University of Udine, Via delle Scienze 206, 33100 Udine, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8404-3187","authenticated-orcid":false,"given":"Manuela","family":"Farinosi","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Computer Science and Physics, University of Udine, Via delle Scienze 206, 33100 Udine, Italy"}]},{"given":"Alberto","family":"Foresti","sequence":"additional","affiliation":[{"name":"Polytechnic of Turin, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-8425-6892","authenticated-orcid":false,"given":"Gian Luca","family":"Foresti","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Computer Science and Physics, University of Udine, Via delle Scienze 206, 33100 Udine, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,28]]},"reference":[{"key":"ref_1","unstructured":"Blake, J.S. 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