Project details

School of Electrical & Electronic Engineering


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Proj No. A3239-251
Title Object Detection in X-Ray Baggage Screening Using Artificial Intelligence
Summary The objective of this project is to apply state of the art deep learning techniques to detect suspicious items (contraband, weapons, prohibited goods etc.) from Xray baggage images. Currently, manual inspection is often slow, inconsistent, and prone to human error. Additionally, Xray images pose the additional challenges such as low contrast and overlapping objects, making detection difficult. The aim is to develop a robust detection model that can automatically identify suspicious items within the baggage to improve accuracy and efficiency.
Supervisor A/P Yap Kim Hui (Loc:S2 > S2 B2B > S2 B2B 53, Ext: +65 67904339)
Co-Supervisor -
RI Co-Supervisor -
Lab Computer Engineering II (Loc: S2-B3b-08)
Single/Group: Single
Area: Digital Media Processing and Computer Engineering
ISP/RI/SMP/SCP?: