To shorten a waiting time for a belongings inspection, the present invention provides a detection system 1 including a plurality of detection apparatuses 20 and a control apparatus 10. The control apparatus 10 includes a setting unit 11 that sets, for each of the detection apparatuses 20, at least one piece of pre-registered referrable data as reference data. The detection apparatus 20 includes an electromagnetic wave transmission/reception unit 22 that irradiates an electromagnetic wave having a wavelength of equal to or more than 30 micrometers and equal to or less than one meter and receives a reflection wave, and a detection unit 21 that performs, based on a signal of the reflection wave, detection processing based on the reference data being set for each of the detection apparatuses 20.

To shorten a waiting time for a belongings inspection, the present invention provides an inspection system 10 including an acquisition unit 11 that acquires target person identification information identifying an inspection target person, a determination unit 12 that determines, based on target person information stored in association with the target person identification information, reference data referred to in a belongings inspection for the inspection target person, an electromagnetic wave transmission/reception unit 14 that emits an electromagnetic wave having a wavelength of equal to or more than 30 micrometers and equal to or less than one meter and receives a reflection wave, and a detection unit 13 that executes, based on a signal of the reflection wave and the reference data, detection processing.

In example embodiments, a computing system is capable of (a) receiving image data that represents a scene that was scanned by a detection device of a security screening system, (b) based at least on the image data, at least one neural network, and a confidence threshold defined for the security screening system, determining that the image data includes an identified item that has been deemed to be of interest, (c) based at least on determining that the image data includes the identified item that has been deemed to be of interest and one or more security parameters for the security screening system, determining that the identified item is deemed to be a security interest for the security screening system, and (d) based at least on determining that the identified item is deemed to be a security interest for the security screening system, presenting a visualization corresponding to the identified item.

A method includes receiving, from a plurality of magnetic field receivers including magnetic sensors, data characterizing samples obtained by the plurality of magnetic field receivers, the samples of a combination of a first magnetic field and a second magnetic field resulting from interaction of the first magnetic field and an object; determining, using the received data, a polarizability index of the object, the polarizability index characterizing a magnetic polarizability property of the object; classifying, using the determined polarizability index, the object as threat or non-threat; and providing the classification. Related apparatus, systems, techniques, and articles are also described.

An automatic generation system of a training image and a method thereof are provided. The disclosure generates a training image and records the target category and the target position. The disclosure adds the target image to the container image as a candidate image, calculates a reliability of the candidate image, and repeatedly executes the process until the reliability of the candidate image meets a threshold condition for generating the training image. The disclosure is able to generate the training images automatically, and the recognition difficulty of the training image is adjustable by the user, so as to be suitable for customized recognition training.

In an embodiment, a method for generating contrastive information for a classifier prediction comprises receiving image data representative of an input image, using a deep learning classifier model to predict a first classification for the input image, evaluating the input image using a plurality of classifier functions corresponding to respective high-level features to identify one or more of the high-level features absent from the input image, and identifying, from among the high-level features absent from the input image, a pertinent-negative feature that, if added to the input image, will result in the deep learning classifier model predicting a second classification for the modified input image, the second classification being different from the first classification. In an embodiment, the method includes creating a pertinent-positive image that is a modified version of the input image that has the first classification and fewer than all superpixels of the input image.

A system and method for automatically detecting prohibited materials in a compartment at a security checkpoint includes receiving a three-dimensional representation of a compartment from an imaging device connected to the computing system, and classifying each voxel of the three-dimensional representation using a trained neural network to determine whether any voxel classifications of the three-dimensional representation correspond to a voxel classification of a prohibited material.

New software systems and capabilities that facilitate the rapid development, evaluation, and deployment of advanced inspection and detection systems using high-fidelity synthetic imagery. The present invention generates high-fidelity synthetic imagery for detection systems that analyze data across the electromagnetic spectrum in an automated, random, directed, or semi-directed manner.

The present invention relates to a system and method for inspecting object using a plurality of interlacing radiation energies. The system comprising a radiation module configured for producing and capturing radiation in multiple energy levels to scan the content of the cargo and converting the captured radiation into a plurality of images; and a controller configured for signalling the radiation module to start or to stop producing radiation and for controlling the energy level and pulse frequency of the radiation produced by the radiation module. The system further comprising a processor configured for determining whether the cargo contains any contraband or not by analysing the plurality of images, classifying the cargo based on types of materials and substance groups and highlighting region on an analysed image of the same substance by bounding perimeter of the object within a material-colour image for the material.

Disclosed is an apparatus for generating X-ray data including a processor that receives first image data indicating that a hidden item is hidden in a non-hidden item, and second image data indicating the non-hidden item, and generates output data and a buffer. The processor includes an extraction unit that extracts first hidden data corresponding to the hidden item from the first image data, a shape change unit that generates second hidden data by performing a shape change on the first hidden data, an interpolation unit that generates third image data by performing interpolation based on the second image data and the second hidden data, and a projection unit that generates the output data by projecting the third image data onto a 2D plane. The buffer stores a plurality of parameters associated with generation of the first hidden data, the second hidden data, the third image data, and the output data.