Image Recognition and Threat Detection in Bags Arriving at the Airport

International transport security policy requires the baggage screening. In airports and railway stations, these operations are processed manually with the help of X-ray or computed tomography machines. There is a need for an automatic system which could reduce the time of the screening process and possibly, increase the accuracy of the detections. More than that, there is a demand for developing and evaluating methodologies for learning on 3D image-like data, which has been addressed only recently, mostly in the field of medical imaging. The main objective of this research is to develop a framework for object detection in 3D computed tomography scans for high-throughput security applications. In this paper, a literature review on the topic of 3D image recognition is presented, and a transfer learning approach is evaluated on the security risk detection task in X-ray images.