Abstract: A video generating method and apparatus, a storage medium, and a terminal device are provided. The method includes: acquiring current input data of a camera including audio input data and/or image input data; determining an icon to be rendered based on the current input data; rendering the icon to be rendered on a target capturing picture to obtain a capturing effect picture; and generating a target video based on the capturing effect picture. The audio input data includes a preset duration of continuous audio frame data with a current input audio frame of the camera as an ending frame, and the image input data includes a preset number of continuous video frame pictures with a current capturing picture of the camera as the ending frame. The target capturing picture includes the preset number of continuous video frame pictures with the current capturing picture of the camera as a starting frame.

Abstract: In some examples, an electronic device includes a machine learning circuit to detect a user break from an online meeting based on a video stream. In some examples, the machine learning circuit is to send an indicator in response to detecting the user break. In some examples, the electronic device includes a processor coupled to the machine learning circuit. In some examples, the processor is to replace a portion of the video stream with substitute video in response to the indicator.

Abstract: An example system includes: a landmark detection engine to detect landmark positions of landmarks in images based on facial detection; an optical flow landmark engine to determine the landmark positions in the images based on optical flow of the landmarks between the images; a landmark difference engine to determine, for a landmark in a given image: a distance between a detected landmark position and an optical flow landmark position of the landmark; and a weighted landmark determination engine to determine, for a first and second image, a position for the landmark in the second image based on: a respective detected landmark position and a respective optical flow position of the landmark in the second image; and respective distances, determined with the landmark difference engine, between a first detected landmark position of the landmark in the first image and respective optical flow landmark positions for the first and second images.

Abstract: In some examples, with respect to asymmetric-man-in-the-middle capture based application sharing protocol traffic recordation, a dynamic-link library that alters application programming interface calls with respect to communication between an application sharing protocol client and an application sharing protocol server may be injected into the application sharing protocol client. Based on the injected dynamic-link library, data from the communication between the application sharing protocol client and the application sharing protocol server may be ascertained. Further, based on the ascertained data, a test script may be generated to test operation of an application associated with the communication between the application sharing protocol client and the application sharing protocol server.

Abstract: In examples, an electronic device is provided. The electronic device includes a processor to receive an input image from an image sensor. The processor is also to scale a size of the input image to a programmed size. The processor is also to encode the scaled input image to provide a feature map having a fractional size of the scaled input image. The processor is also to process the feature map according to lite reduced atrous spatial pyramid pooling (LR-ASPP) to provide a LR-ASPP result. The processor is also to decode the LR-ASPP result to provide an image segmentation result.

Abstract: Examples of methods for training using rendered images are described herein. In some examples, a method may include, for a set of iterations, randomly positioning a three-dimensional (3D) object model in a virtual space with random textures. In some examples, the method may include, for the set of iterations, rendering a two-dimensional (2D) image of the 3D object model in the virtual space and a corresponding annotation image. In some examples, the method may include training a machine learning model using the rendered 2D images and corresponding annotation images.

Abstract: A first machine learning model is applied to an image of a person and a stationary object to generate a first intermediate image including a simplified pose representation of the person in the image corresponding to a pose of the person. A simplified representation of the stationary object in the image is added to the first intermediate image. The simplified representation includes key points of the stationary object in the image. A second machine learning model is applied to a second intermediate image corresponding to the first intermediate image to determine a state of the person relative to the stationary object in the image as either a first state or a second state.

Abstract: An example device is described for facilitating polygon localization. In various aspects, the device can comprise a processor. In various instances, the device can comprise a non-transitory machine-readable memory that can store machine-readable instructions. In various cases, the processor can execute the machine-readable instructions, which can cause the processor to localize a polygon depicted in an image, based on execution of a deep learning pipeline. In various aspects, the deep learning pipeline can comprise a circular-softmax block.

Abstract: A device includes a display panel and a processor. The processor is to receive information corresponding to an image displayed on the display panel and determine whether a relevant portion of the image is centered with respect to an area of interest of the display panel. The processor is further to responsive to a determination that the relevant portion of the image is not centered with respect to the area of interest of the display panel, perform an operation to cause the relevant portion of the image to be adjusted such that the relevant portion of the image is centered with respect to the area of interest of the display panel.

Abstract: In some examples in accordance with the present description, an electronic device is provided. The electronic device includes an image sensor and a controller. The controller is to receive multiple images from the image sensor including respective foregrounds and backgrounds. The controller is also to segment the respective foregrounds from the backgrounds. The controller is also to combine the backgrounds to form a fused background. The controller is also to receive a new image including a new image foreground and a new image background. The controller is also to segment the new image foreground from the new image background.

Abstract: In some examples in accordance with the present description, an electronic device is provided. The electronic device includes a controller to implement an image segmentation process. The controller is to obtain color information of an image. The controller also is to obtain depth information of the image. The controller also is to determine a depth of a face represented in the color information. The controller also is to segment a foreground of the image from a background of the image according to the color information and the depth information based on the depth of the face.

Abstract: An alkali metal reactor power supply, including: a reactor vessel, the bottom part of which is provided with a liquid alkali metal; a reactor core, which is arranged in the reactor vessel and includes a plurality of fuel rods and a radial reflection layer arranged at the periphery of the plurality of fuel rods, wherein the surface of each fuel rod is provided with a first liquid absorption core, the bottom part of the reactor core is provided with second liquid absorption cores which are connected to the first liquid absorption cores, and the second liquid absorption cores can be in contact with the liquid alkali metal; and alkali metal thermoelectric converters, which are arranged along the circumferential direction of the radial reflection layer, and divide the inside of the reactor vessel into a high-pressure steam chamber located above the alkali metal thermoelectric converters and a low-pressure steam chamber located below the alkali metal thermoelectric converters.

Abstract: A saliency map of an image is generated. Saliency regions of the saliency map are identified. The saliency regions are merged into a combined saliency region. Candidate image crops of the image are generated based on the combined saliency region. An image crop of the image is selected from the candidate image crops using a machine learning model.

Abstract: An example system includes a landmark engine to detect a facial landmark in an image of a face. The system includes a comparison engine to determine a difference between the facial landmark in the image and a facial landmark of a neutral face. The system also includes an action engine to determine whether a facial action unit occurred based on whether the difference satisfies a condition.

Abstract: In some examples, an electronic device comprises an interface to receive a video of a human face, a memory storing executable code, and a processor coupled to the interface and to the memory. As a result of executing the executable code, the processor is to receive the video from the interface, use a facial detection technique to produce a sequence of images of the human face based on the video, use a neural network to predict a photoplethysmographic (PPG) signal based on the sequence of images, convert the PPG signal to a frequency domain signal, and determine a heart rate by performing a frequency analysis on the frequency domain signal.

Abstract: A region of interest is extracted from a captured image of a physical object. An autoencoder model is applied to the extracted region of interest to reconstruct the region of interest. A location of an anomaly of the physical object within the extracted region of interest, if any, is identified based on the extracted and reconstructed regions of interest.

Abstract: In some examples, a non-transitory computer-readable medium stores executable code, which, when executed by a processor, causes the processor to receive a video of at least part of a human torso, use a neural network to produce multiple vector fields based on the video, the multiple vector fields representing movement of the human torso, and determine a respiration rate of the human torso using the multiple vector fields.

Abstract: Examples of methods for image enhancement are described. In some examples, a method includes segmenting an image into an object region and a background region. In some examples, the image has a first resolution. In some examples, the method includes generating, using a first machine learning model, an enhanced object region with a second resolution that is greater than the first resolution. In some examples, the first machine learning model has been trained based on object landmarks. In some examples, the method includes generating, using a second machine learning model, an enhanced background region with a third resolution that is greater than the first resolution. In some examples, the method includes combining the enhanced object region and the enhanced background region to produce an enhanced image.

Abstract: The invention discloses a method for preparing graphene by mechanical exfoliation and application thereof. The method includes the following steps of: (1) dispersing graphite raw material in a foaming agent aqueous solution to obtain a graphite pre-dispersing solution; and (2) subjecting the graphite pre-dispersing solution to milling, washing with water, and centrifugal classification, to obtain the graphene; wherein the foaming agent aqueous solution includes the following components: sodium alpha-olefin sulfonate, sodium alcohol ether sulphate, diethanolamine coconut fatty acid, polyethylene glycol, and water. In the invention, the foaming agent produce a large amount of stable and fine foam in a closed milling cavity, which can produce jostle effect, support the graphite, and increase the contact area between the graphite and the milling medium, so as to achieve good exfoliation effect.

Abstract: A salfaprodil freeze-dried powder injection, and a preparation method thereof and the use thereof are proposed. The preparation method may include adding salfaprodil into water for injection, filtering after the salfaprodil is completely dissolved, and adjusting pH of filtrate with an alkaline substance water solution. The method may also include adding the injection water to achieve a constant volume, filling with an inert gas for protection, and performing sterilization and filtration to obtain a salfaprodil solution, which is then freeze-dried to obtain the -salfaprodil freeze-dried powder injection.