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http://dx.doi.org/10.17661/jkiiect.2021.14.2.149

A Study on Fuzzy Searching Algorithm and Conditional-GAN for Crime Prediction System  

Afonso, Carmelita (Korea Univ. of Tech. & Edu., Graduate School, Drpartment of Computer Eng.)
Yun, Han-Kyung (School of Computer Science and Engineering, Korea University of Technology and Education)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.14, no.2, 2021 , pp. 149-160 More about this Journal
Abstract
In this study, artificial intelligence-based algorithms were proposed, which included a fuzzy search for matching suspects between current and historical crimes in order to obtain related cases in criminal history, as well as conditional generative adversarial networks for crime prediction system (CPS) using Timor-Leste as a case study. By comparing the data from the criminal records, the built algorithms transform witness descriptions in the form of sketches into realistic face images. The proposed algorithms and CPS's findings confirmed that they are useful for rapidly reducing both the time and successful duties of police officers in dealing with crimes. Since it is difficult to maintain social safety nets with inadequate human resources and budgets, the proposed implemented system would significantly assist in improving the criminal investigation process in Timor-Leste.
Keywords
Crime Prediction System; Fuzzy Searching Algorithm; Generative Networks; CGAN; AI;
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