Methods and systems are disclosed for displaying an augmented reality virtual object on a multimedia device. One method comprises detecting, in an augmented reality environment displayed using a first device, a virtual object; detecting, within the augmented reality environment, a second device, the second device comprising a physical multimedia device; and generating, at the second device, a display comprising a representation of the virtual object.

An improvement to automatic classifying of threat level of objects in CT scan images of container content, methods include automatic identification of non-classifiable threat level object images, and displaying on a display of an operator a de-cluttered image, to improve operator efficiency. The de-cluttered image includes, as subject images, the non-classifiable threat level object images. Improvement to resolution of non-classifiable threat objects includes computer-directed prompts for the operator to enter information regarding the subject image and, based on same, identifying the object type. Improvement to automatic classifying of threat levels includes incremental updating the classifying, using the determined object type and the threat level of the object type.

A face image processing method and apparatus, a face image display method and apparatus, and a device are provided, belonging to the technical field of image processing. The method includes: acquiring a first face image of a person; invoking an age change model to predict a texture difference map of the first face image at a specified age, the texture difference map being used for reflecting a texture difference between a face texture in the first face image and a face texture of a second face image of the person at the specified age; and performing image processing on the first face image based on the texture difference map to obtain the second face image.

Systems and methods include an image capture component configured to capture infrared images of a scene, and a logic device configured to identify a target in the images, acquire temperature data associated with the target based on the images, evaluate the temperature data and determine a corresponding temperature classification, and process the identified target in accordance with the temperature classification. The logic device identifies a person and tracks the person across a subset of the images, identify a measurement location for the target in a subset of the images based on target feature points identified by a neural network, and measure a temperature of the location using corresponding values from one or more captured thermal images. The logic device is further configured calculate a core body temperature of the target using the temperature data to determine whether the target has a fever and calibrate using one or more black bodies.

A computer-implemented method is provided for improving live video quality. The method comprises: acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject, and the stream of consecutive image frames are acquired with reduced amount of radiation dose; applying a deep learning network model to the stream of consecutive image frames to generate an image frame with improved quality; and displaying the image frame with improved quality in real-time on a display.

A program and the like that make a catheter system relatively easy to use. The program including a non-transitory computer-readable medium (CRM) storing computer program code executed by a computer processor that executes a process comprising: acquiring a tomographic image generated using a diagnostic imaging catheter inserted into a lumen organ; and inputting the acquired tomographic image to a first model configured to output types of a plurality of objects included in the tomographic image and ranges of the respective objects in association with each other when the tomographic image is input, and outputting the types and ranges of the objects output from the first model.

An image processing method, an electronic device and a computer storage medium are provided, which relates to the fields of computer vision, augmented reality and artificial intelligence technologies. An implementation includes: acquiring a to-be-processed face image; reconstructing a face based on the to-be-processed face image to obtain a first blend coefficient vector based on a first blendshape base group; mapping the first blend coefficient vector to a second blendshape base group according to a pre-obtained coefficient mapping matrix between the first blendshape base group and the second blendshape base group to obtain a second blend coefficient vector based on the second blendshape base group; acquiring input face adjustment information, the face adjustment information including second blendshape base information; and obtaining a target face image based on the second blendshape base information and the second blend coefficient vector.

The present invention discloses a system and method for simulating radio frequency (RF) signal propagation through a plurality of mediums using a plurality of configurable digital representations of building information model in two dimensional (2D) or augmented reality (AR) or virtual reality (VR) environments. The system comprising: a client interface, a processor and a memory. The processor comprising a building information model (BIM) generation unit, RF equipment conversion unit and a RF propagation prediction unit. The BIM generation unit is configured to translate 2D graphics into BIM data-sets, by reference to administrator input, to act as one or more parameters to control a generation of 2D or AR or VR environments. The RF equipment conversion unit is configured to transform adjunct data related to a physical configuration of one or more RF equipment into data models. The RF propagation prediction unit is configured to utilize the one or more parameters and the transformed data related to the physical configuration of the one or more RF equipment for simulating the RF signal propagation pattern predictions through the plurality of mediums.

The present disclosure relates to a portable production machine, a mobile terminal, a production system having a portable production machine and a mobile terminal, and a method for capturing data. According to aspects of the disclosure, on the production machine - which can be, for example, a welding machine or cutting machine - production data is automatically captured, organized into data sets, and converted into data set images, which are displayed on a display device. The displayed data set images are captured with a mobile terminal and transmitted to a central server. As a result, a plurality of production machines can be incorporated into a data system without the need for any changes to the hardware in the production machines.

A hazard visualization system that can use artificial intelligence to identify locations at which hazards have occurred and a cause therein and to predict locations at which hazards may occur in the future is described herein. As a result, the hazard visualization system may reduce the likelihood of structural damage and/or loss of life that could otherwise occur due to natural disasters or other hazards. For example, the hazard visualization system can train an artificial intelligence model to predict the date, time, type, severity, path, and/or other conditions of a hazard that may occur at a geographic location. As another example, the hazard visualization system can train an artificial intelligence model to identify equipment or other infrastructure depicted in geographic images.