Airport Screening for Threat Detection Via Super Resulted and Sharpened Data
People basically prefer a runway for air transportation through airports. These are the places where airplanes land and gets take offs. This transportation prefers for large distance travelling. The baggage’s are the basic necessity for the passengers. If the passengers carry some dangerous items like pin, screw, knife, gun, blade, spring, shuriken, and other metal items and some electronic gadgets which don’t have authorizations. This all leads to scarce situation and bizarre state in airports. Therefore, the airport screening should be must involve in thorough scanning. The proposal of this project is that if embed the detection model in the scanner of the machine, it alerts the nearby security agents when a threat item is detected. The work deals with software side of the security inspection. To train and test for the detection of the threat, we gather the X-ray images related to the airport baggage. The development of our proposed model is done through Deep Learning (DL) and Computer Vision (CV) algorithms to detect the threat items. The algorithms enlarge the images and analyzes the area of threat items.
Authors
- Aravind Karrothu (ORCID: https://orcid.org/0000-0003-4389-2785)
- Ramachandro Majji (ORCID: https://orcid.org/0000-0002-0297-8518)
- Avinash Kishore (ORCID: https://orcid.org/0000-0003-4625-4922)
- D. Shalini
Publication Details
- Journal
- Journal of Neonatal Surgery
- Published
- 2025-03-24
- DOI
- https://doi.org/10.52783/jns.v14.2559
- Primary Topic
- Air Traffic Management and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00