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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Forensic Event Analysis: From Seemingly Unrelated Data to Understanding

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Padilha, Rafael [1] ; Rodrigues, Caroline Mazini [2] ; Andalo, Fernanda [2] ; Bertocco, Gabriel [3] ; Dias, Zanoni [4] ; Rocha, Anderson [4]
Total Authors: 6
[1] Univ Estadual Campinas, Comp Sci, Inst Comp, Campinas - Brazil
[2] Univ Estadual Campinas, Campinas - Brazil
[3] Univ Estadual Campinas, Comp Sci, Digital Forens, Campinas - Brazil
[4] Univ Estadual Campinas, Inst Comp, Campinas - Brazil
Total Affiliations: 4
Document type: Journal article
Source: IEEE SECURITY & PRIVACY; v. 18, n. 6, p. 23-32, NOV 2020.
Web of Science Citations: 0

We discuss the problem of restructuring visual data from different heterogeneous sources to analyze an event of interest. We present X-coherence: a pipeline seeking to organize and represent pieces of data, tying them coherently with the real world and with one another. We also outline research challenges while seeking X-coherence. (AU)

FAPESP's process: 18/16214-3 - Heterogeneous data analysis for event detection
Grantee:Caroline Mazini Rodrigues
Support type: Scholarships in Brazil - Master
FAPESP's process: 17/21957-2 - Learning Visual Clues of the Passage of Time
Grantee:Rafael Soares Padilha
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events
Grantee:Anderson de Rezende Rocha
Support type: Research Projects - Thematic Grants