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Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response.

, , , , and . ASONAM, page 151-158. IEEE, (2020)

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Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response., , , , and . ASONAM, page 151-158. IEEE, (2020)HumAID: Human-Annotated Disaster Incidents Data from Twitter, , , and . (2021)cite arxiv:2104.03090Comment: Accepted in ICWSM-2021, Twitter datasets, Textual content, Natural disasters, Crisis Informatics.Mapping Flood Exposure, Damage, and Population Needs Using Remote and Social Sensing: A Case Study of 2022 Pakistan Floods., , , , , , and . WWW, page 4120-4128. ACM, (2023)A Real-Time System for Detecting Landslide Reports on Social Media Using Artificial Intelligence., , , , , , and . ICWE, volume 13362 of Lecture Notes in Computer Science, page 49-65. Springer, (2022)AI for Disaster Rapid Damage Assessment from Microblogs., , , , and . AAAI, page 12517-12523. AAAI Press, (2022)Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence., , , , and . ISCRAM, page 761-773. ISCRAM Digital Library, (2020)Analyzing Mentions of Death in COVID-19 Tweets., , , and . ICWSM, page 2077-2083. AAAI Press, (2024)Flood Insights: Integrating Remote and Social Sensing Data for Flood Exposure, Damage, and Urgent Needs Mapping., , , , , and . AAAI, page 22716-22724. AAAI Press, (2024)HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks., , , and . ICWSM, page 933-942. AAAI Press, (2021)