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- W4380343270 abstract "Most often, users use ATMs to withdraw cash from automated electronic machines. When used, a client doesn't need assistance from a bank employee to handle monetary changes. In the current set-up, many people who take cash from an ATM are vulnerable to robberies and theft since there aren’t enough protections in place. ATM banks are increasingly installing surveillance cameras, but police forces' ability to keep tabs on the footage has lagged behind. Attempts may be made to steal the money from an ATM by breaking into the machine or by damaging it in a defamatory manner. As a preventative measure, we will equip the ATM with a camera module permanently installed in the room to conduct continual video monitoring. Humans and the activities they take inside the ATM while attempting to break in are identifiable to the camera. Consequently, this software is concerned with the programme created to automate video monitoring and identify any fraudulent actions occurring at ATMs. Such algorithms may be used to identify people in a photo, locate, and follow the camera as it moves and ultimately determine what steps should be taken to avoid illegal behaviour. As a result, we determined whether or not the assault was indeed taking place and notified the police. The ability to foresee an impending assault is a significant advantage." @default.
- W4380343270 created "2023-06-13" @default.
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- W4380343270 date "2023-01-01" @default.
- W4380343270 modified "2023-09-27" @default.
- W4380343270 title "ATM Theft Detection Using Artificial Intelligence" @default.
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- W4380343270 doi "https://doi.org/10.1007/978-981-99-1909-3_45" @default.
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