The invention concerns a method and a system (1) for detecting a threat in a shoe (21, 22) worn by an individual (2) accessing a restricted access area (50) through a security access point (51). The method comprises obtaining a first response provided by a first metal detector (11) by sensing a pair of shoes worn by the individual. The first response is compared with a signature signal representing a shoe comprising a threat or an object representing a threat so to indicate a critical pair of shoes. In such case, the method further comprises prompting the individual to place the critical pair of shoes at a predefined position to obtain a second response provided by the first or by a second metal detector (12, 13) by sensing one shoe of said critical pair of shoes. A potential threat is detected by comparing the second response with the signature signal.

Automatic threat detection of volumetric computed tomography (CT) data, including: extracting at least one 3-D object from the volumetric CT data; constructing a feature vector for each of the at least one 3-D objects; and classifying each 3-D object as one of a threat or benign object using the feature vector and a set of truth threat and benign objects.

The present invention is directed to an inspection system that has a radiation source, a detector array, an inspection region, and a processing unit, where the processing unit a) obtains a radiographic image, b) segments the radiographic image based on radiation attenuation or transmission, c) identifies at least one segmented area on the radiographic image, d) filters the at least one segmented area using at least one geometric filter, e) generates feature vectors using the filtered segmented area; and f) compares the feature vectors against predefined values to determine whether a high-atomic-number object is present.

The present invention is a multi-threat detection method and system for high-traffic areas, such as airports, other mass-transit hubs, malls, symposiums, and the like. The detection methodology comprises a set of detection blocks, each performing different functions, and taking the information resulting from each block and entering it into one or more detection algorithms. The blocks comprise microwave detectors, co-polarization versus cross-polarization processors, magnetometers, and cameras (optional). The values calculated by the blocks are entered into machine learning algorithms which detect a threat if a threshold value is met. The detection occurs at a distance and the alarm may be silent, such that authorities are able to address threats without the target being aware. The alarm is also able to differentiate among varying threats based on the values calculated. No shadowing problems exist, and thus several targets may be monitored simultaneously without slowing down the speed of processing.

Systems and method to detect presence of buried landmines in a suspect area. A drone is outfitted with a ground penetrating radar, an infrared camera, and a metal detector mounted onto a leveling platform. The drone is flown over the suspect area while maintaining the leveling platform horizontal. Signals from the ground penetrating radar, an infrared camera, and a metal detector are converted into radargram, thermal image, and metal gram. Convolutional neural networks are applied to each of the into radargram, thermal image, and metal gram to detect anomalies.

A terahertz security inspection robot is provided, including: a housing including a main housing and a head housing rotatably connected to the main housing; a terahertz wave imaging mechanism including a mirror assembly arranged in the head housing and a detector array arranged in the main housing; and a rotating mechanism configured to cause the head housing and the mirror assembly located in the head housing to rotate with respect to the main housing, so that the mirror assembly of the terahertz wave imaging mechanism is oriented in different directions to respectively perform terahertz scanning and imaging on objects to be inspected in different inspection regions in a security inspection scene.

An intelligent assistant records speech spoken by a first user and determines a self-selection score for the first user. The intelligent assistant sends the self-selection score to another intelligent assistant, and receives a remote-selection score for the first user from the other intelligent assistant. The intelligent assistant compares the self-selection score to the remote-selection score. If the self-selection score is greater than the remote-selection score, the intelligent assistant responds to the first user and blocks subsequent responses to all other users until a disengagement metric of the first user exceeds a blocking threshold. If the self-selection score is less than the remote-selection score, the intelligent assistant does not respond to the first user.

Various embodiments are directed toward systems and methods relating to security screening. For example, a screening system includes chamber scanners oriented to scan different heights corresponding to different respective portions of a user, to identify whether the user is carrying an item that is to be divested. The screening system also includes a divestment scanner configured to obtain a detailed item characterization of the item divested from the user.

The present disclosure relates to an intelligent prevention passage control system for an electronic device, which comprises a detection device for an electronic device, a traffic control device integrated with the detection device for the electronic device, an industrial control host, a server, an access controller and a management terminal inside the traffic control device. The present disclosure can more accurately judge violations by scoring violations, and can make the system more intelligent by accurately judging violations, thus realizing no manual attendance, solving the problems of personnel recruitment, shift attendance and personnel management, and saving a lot of labor cost. At the same time, the system can avoid the hidden dangers caused by human feelings, sense of responsibility and inertia brought by manual prevention, and ensure the consistent, accurate and reliable standards of detection work.

Provided are an object identification device and an object identification method in which objects can be easily identified. The object identification device is provided with a pixel group extraction unit which scans, in units of the image area, an X-ray transferred image obtained from an imaging unit which performs X-ray imaging to an item to be inspected that is supplied, and extracts a plurality of pixel groups including characteristics of a shape of at least a part of the item to be inspected, and a determination unit which determines, with regard to the plurality of pixel groups extracted by the pixel group extraction unit, whether the item to be inspected corresponds to the object by executing all of the series of mappings related to an angle of an n direction by using each of the weight parameters based on the data group read from the memory unit.