Manifold Learning for Real-World Event Understanding

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Jan 2021Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Information Forensics and Security, volume 16, pages 2,957-2,972 (issn: 1556-6013, eissn: 1556-6021,

Copyright policy )

Authors: Caroline Mazini Rodrigues; Aurea Soriano-Vargas; Bahram Lavi; Anderson Rocha 0001; Zanoni Dias;

doi: 10.1109/tifs.2021.3070431 , 10.5281/zenodo.4633315 , 10.60692/p3t2t-rjs46 , 10.60692/7h8s3-pcf47 , 10.5281/zenodo.4633316

Manifold Learning for Real-World Event Understanding

- Summary
- Subjects
- Metrics

Abstract

Supplementary Material and datasets of the paper Manifold Learning for Real-World Event Understanding. It includes 5 datasets: - Wedding: royal wedding which happened on April 29th, 2011 at the Westminster Abbey; - Fire: Notre Dame cathedral fire which happened on April 15th, 2019; - Bombing: Boston Marathon bombing which happened on April 15th, 2013; - National Museum: Brazilian national museum fire which happened on September 2nd, 2018; - Bangladesh Fire: Bangladesh fire which happened on February 20th, 2019.

This work was funded by the Brazilian funding agency CAPES under the grant Capes Deep-Eyes, and the São Paulo Research Agency FAPESP under the grant DéjàVu 2017/12646-3 and grants 2013/08293-7, 2015/11937-9, 2017/16246-0, 2017/16871-1, 2018/16214-3, 2018/05668-3 and 2018/16548-9. Additional funding was awarded by the CNPq under grants 400487/2016-0, 425340/2016-3, 304380/2018-0, and 304497/2018-5.

Related Organizations

State University of Campinas
Brazil

Keywords

Digital Epidemiology and Disease Surveillance, Artificial intelligence, Epidemiology, FOS: Political science, FOS: Law, Quantum mechanics, Visual Object Tracking and Person Re-identification, Data science, Anomaly Detection in High-Dimensional Data, Social media, Event Understanding and Reconstruction, Artificial Intelligence, Health Sciences, Machine learning, Image Representation, Event (particle physics), Political science, Social Media Analysis, Event data, Physics, Politics, Manifold Learning, Image Components, Computer science, World Wide Web, Digital Forensics, Computer Science, Physical Sciences, Multiple Object Tracking, Medicine, Computer Vision and Pattern Recognition, Representation (politics), Law

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	3
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average