Next Generation Threat Detection Enhances Safety and Efficiency

Automated threat detection in X-ray machines is a vital area of research that aims to enhance the security and efficiency of screening processes in various domains, such as aviation, transportation, e-commerce, urban security, and cargo. X-ray machines are commonly used for scanning bags, luggage, parcels, and other items for potential threats, including explosives, weapons, drugs, and contraband. However, the current screening process heavily relies on human operators with limitations in accuracy, speed, and consistency. Additionally, human operators are susceptible to fatigue, boredom, distraction, and bias, which can affect their performance and compromise safety.

Automating the threat detection process has been a challenging task. Still, researchers have proposed various methods to overcome these difficulties using artificial intelligence (AI) techniques like machine learning and deep learning. These methods train computer algorithms to recognise and classify threat objects in X-ray images based on their shape, size, density, colour, and other features. AI-based threat detection has several advantages, including improved accuracy, speed, and consistency.

Some advantages of using AI for threat detection are:

AI algorithms can detect threats beyond human capabilities, irrespective of size, occlusions, and angles. Additionally, they can help reduce false alarm rates and quickly adapt to new threats, ensuring high detection accuracy.

One of the most significant advantages of AI algorithms is their continuous improvement. They can learn from data and feedback, allowing them to update themselves remotely and enhance their performance by leveraging data from multiple sources and domains.

AI detection algorithms can increase the throughput of screening processes by reducing manual procedures and minimising the need for human intervention. They can also reduce labour costs and training requirements and eliminate redundant checks by supervisors, resulting in greater operational efficiency.

Lastly, AI algorithms can run on commercial off-the-shelf hardware, contributing to a low total cost of ownership. They can extend the product life cycle of existing machines, making them a cost-effective solution for businesses.

Neural Guard has developed a cutting-edge solution called EyeFox, which utilises AI technology to provide high-accuracy threat detection for X-ray security screening operators. By quickly and accurately distinguishing between threats and other items, EyeFox minimises close contact with bag contents and people, leading to increased efficiency and throughput. Neural Guard has built a vast data set of over 3 million images of threat and non-threat items, which is used to train the detection algorithm and reduce false alarms. This data set is constantly updated with new images and orientations, and EyeFox operates on a wide range of X-ray systems.

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