Abstract
Airports are the places where landings and take offs of the flights take place. In general, airports are preferred for traveling over large distances. While traveling in flights we carry our baggage which consists of various items, but the items that are prohibited in the baggage are scissors, knives, gun, and the electronic devices which cannot be switched off. Carrying dangerous items may lead to hijacking of flights and it even led to unusual situations in the airport. To prevent public from threat, airports generally have security inspection in which you will be required to pass your luggage through an X-ray machine where it will be checked for dangerous items. This analysis deals with software side of the security inspection and it is a brief study on various state-of-art proposed deep learning intended methods that are used to detect threat in baggage screening, advantages of their methodology, limitations, and gaps to be implemented.
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