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Title:Zanesljivost uporabe orodij strojnega učenja pri policijskem delu : diplomsko delo visokošolskega študijskega programa Varnost in policijsko delo
Authors:ID Turk, Rok (Author)
ID Mihelič, Anže (Mentor) More about this mentor... New window
ID Modic, Maja (Comentor)
Files:.pdf VS_Turk_Rok_2026.pdf (1,07 MB)
MD5: A1AE9D951B216E32AA9E40110DC95B94
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FVV - Faculty of Criminal Justice and Security
Abstract:Diplomsko delo se nanaša na zanesljivost uporabe orodij strojnega učenja pri policijskem delu. V zadnjih letih se policija sooča s kadrovskim pomanjkanjem, obeti za prihodnost pa so še slabši. Zaradi tega je v določene policijske aktivnosti smotrna vpeljava umetne inteligence, ki je v zadnjih letih revolucionirala svet na vseh področjih. S pomočjo naprednih algoritmov je sposobna analizirati velike količine podatkov, je sposobna prepoznati vzorce in anomalije, ki jih lahko preiskovalci spregledajo. Vse to pa je sposobna narediti v občutno hitrejšem času kot preiskovalci s klasičnim pregledovanjem elektronskih podatkov. Sama uporaba umetne inteligence v policiji prinaša napredek, predvsem pa bi lahko v določeni meri s svojo učinkovitostjo in krajšim časom preiskave podatkov vsaj delno nadomestila pomanjkanje kadra v policiji. V diplomskem delu je predstavljena tuja in domača strokovna literatura ter zakonodaja, ki se navezuje na uporabo orodij strojnega učenja pri policijskem delu. V nadaljevanju so predstavljena orodja strojnega učenja, ki bi lahko bila uporabna za policijsko delo. Na praktičnih primerih je predstavljena uporaba treh različnih orodij s katerimi je mogoče obdelovati večje baze slikovnih, tekstovnih in video datotek. Preizkus orodij je potekal na javno dostopnih bazah podatkov. V zaključku dela pa so predstavljene prednosti in pa omejitve teh orodij za policijsko delo.
Keywords:policijsko delo, orodje strojnega učenja, elektronski podatki, diplomske naloge
Publication status:Published
Publication version:Version of Record
Place of publishing:Ljubljana
Place of performance:Ljubljana
Publisher:R. Turk
Year of publishing:2026
Year of performance:2026
Number of pages:VII f., 53 str.
PID:20.500.12556/DKUM-97801 New window
UDC:351.741:004.89(043.2)
COBISS.SI-ID:283854595 New window
Publication date in DKUM:07.07.2026
Views:260
Downloads:4
Metadata:XML DC-XML DC-RDF
Categories:FVV
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:15.04.2026

Secondary language

Language:English
Title:Reliability of using machine learning tools in police work
Abstract:This work concerns the reliability of the use of machine learning tools in police work. In recent years, the police have been facing a shortage of personnel, and the prospects for the future are even worse. For this reason, it is advisable to introduce artificial intelligence into certain police activities, which has revolutionized the world in all areas in recent years. With the help of advanced algorithms, it is able to analyze large amounts of data, it is able to recognize patterns and anomalies that investigators may overlook. And it is able to do all this in a significantly faster time than investigators with classic electronic data review. The use of artificial intelligence in the police itself brings progress, and above all, it could, to a certain extent, at least partially compensate for the shortage of personnel in the police with its efficiency and shorter data investigation time. The diploma thesis presents foreign and domestic professional literature and legislation related to the use of machine learning tools in police work. The following presents machine learning tools that could be useful for police work. Practical examples demonstrate the use of three different tools that can process larger databases of image, text and video files. The tools were tested on publicly available databases. The conclusion presents the advantages and limitations of these tools for police work.
Keywords:machine learning tools, artificial intelligence, police, police work, electronic data processing


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