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Fire Detection from Social Media Images by Means of Instance-Based Learning.

, , , , , , , and . ICEIS (Revised Selected Papers), volume 241 of Lecture Notes in Business Information Processing, page 23-44. Springer, (2015)

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Modeling Temporal Activity to Detect Anomalous Behavior in Social Media., , , , and . ACM Trans. Knowl. Discov. Data, 11 (4): 49:1-49:23 (2017)RSC: Mining and Modeling Temporal Activity in Social Media., , , , and . KDD, page 269-278. ACM, (2015)MFS-Map: efficient context and content combination to annotate images., , and . SAC, page 945-950. ACM, (2014)Unveiling smoke in social images with the SmokeBlock approach., , , , , , and . SAC, page 49-54. ACM, (2016)dp-BREATH: Heat maps and probabilistic classification assisting the analysis of abnormal lung regions., , , , , , , , , and . Comput. Methods Programs Biomed., (2019)Techniques for Effective and Efficient Fire Detection from Social Media Images., , , , , , , and . ICEIS (1), page 34-45. SciTePress, (2015)Fire Detection from Social Media Images by Means of Instance-Based Learning., , , , , , , and . ICEIS (Revised Selected Papers), volume 241 of Lecture Notes in Business Information Processing, page 23-44. Springer, (2015)VolTime: Unsupervised Anomaly Detection on Users' Online Activity Volume., , , and . SDM, page 108-116. SIAM, (2017)An Efficient Algorithm for Fractal Analysis of Textures., , and . SIBGRAPI, page 39-46. IEEE Computer Society, (2012)Vote-and-Comment: Modeling the Coevolution of User Interactions in Social Voting Web Sites., , , and . ICDM, page 91-100. IEEE Computer Society, (2016)