Deep Learning for Law Enforcement: A Survey About Three Application Domains

Deep learning is rapidly growing, obtaining groundbreaking results in speech recognition, image processing, pattern recognition, and many other application domains. Following the success of deep learning, many automatic data analysis techniques are becoming common also in law enforcement agencies. To this end, we present a survey about the potential impact of deep learning on three application domains, peculiar to law enforcement agencies. Specifically, we analyze the findings about deep learning for Face Recognition, Fingerprint Recognition, and Violence Detection. In fact, combining 1) data from the routine procedure of collecting a subject frontal and profile pictures and her/his fingerprints, 2) the pervasiveness of surveillance cameras, and 3) the capability of learning from a huge amount of data, might support the next steps in crime prevention.

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