Tag Archives: Daniel Moraes

Temporal robust features for violence detection

Automatically detecting violence in videos is paramount for enforcing the law and providing the society with better policies for safer public places. In addition, it may be essential for protecting minors from accessing inappropriate contents on-line, and for helping parents … Continue reading

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Video pornography detection through deep learning techniques and motion information

In this paper, the authors deal with a growing issue of our connected society: automated sensitive media (pornographic, violent, gory, etc.) filtering. A range of applications has increased societal interest on the problem, e.g., detecting inappropriate behavior via surveillance cameras; … Continue reading

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FSI: Pornography classification: The hidden clues in video space–time

We are glad to announce that our journal paper “Pornography classification: The hidden clues in video space–time” has been accepted at Forensic Science International Journal, Volume 268 , 46-61, 2016. In the paper, the authors deal with an important issue … Continue reading

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Low false positive learning with support vector machines

In automated computer-based diagnosis systems, falsely determining that a case is normal is much more serious than falsely determining that the case is abnormal, especially if the system is being used for triage of patients. This is an example where … Continue reading

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RECOD gets 2nd place at Violence Scene Detection MediaEval 2014

RECOD team at MediaEval 2014 (MediaEval Benchmarking Initiative for Multimedia Evaluation) got the 2nd place at the generalization task (YouTube videos) of the Violent Scene Detection competition. The team was formed by Profs. Anderson Rocha, Eduardo Valle and Siome Goldenstein, … Continue reading

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