Enhanced-Precision-and-Efficiency-on-Baggage-Security

In the contemporary security landscape, the safeguarding of passengers and the integrity of baggage emerges as a critical concern. The baggage security system grapples with a multifaceted challenge, primarily revolving around issues of human resources and the accuracy of human operators in detecting concealed contraband items within luggage. In response to these challenges, this paper proposes a paradigm shift through the integration of state-of-the-art Deep Learning techniques. The overarching goal is not only to redefine the efficiency of baggage security systems but also to significantly elevate their accuracy. The focal point of this project is the infusion of intelligence directly into the security system, empowering it to autonomously identify contraband items concealed within baggage. This strategic shift aims to diminish the reliance on human operators, consequently mitigating the potential for human error. By leveraging the power of Deep Learning, the proposed approach holds the promise of revolutionizing baggage security, ensuring a more robust defense against evolving security threats