Abstract: Provided are a liquid crystal grating and a display device. The liquid crystal grating is configured to modulate incident light beams of multiple colors. The light beams include first color light. The liquid crystal grating includes a first substrate, a liquid crystal layer and a second substrate. The liquid crystal layer is located between the first substrate and the second substrate and includes multiple liquid crystal molecules. The liquid crystal grating satisfies that ?n1×d<?1, where ?n1 denotes a refractive index difference of birefringence of the liquid crystal molecules corresponding to the first color light, d denotes the thickness of the liquid crystal layer along the direction perpendicular to a plane on which the first substrate is located, and ?1 denotes the center wavelength of the first color light.

Abstract: Techniques for skin-condition visualization using machine learning. A color image depicting facial skin of a subject is retrieved. A monochromatic version of the color image is generated. Candidate instances of one or more skin conditions are segmented from the monochromatic version based on a segmentation threshold and using a machine learning model. A polarized version of the color image is generated, and based on the polarized version, the candidate instances are filtered. One or more simulation images are generated based on the filtered candidate instances.

Abstract: A display panel and a display device are provided. The display panel includes a first substrate, a second substrate arranged opposite to the first substrate, an electrophoresis layer, a liquid-blocking portion and a supporting structure. The electrophoresis layer is arranged between the first substrate and the second substrate and includes multiple electrophoresis particles. The liquid-blocking portion is arranged at an edge of the first substrate and/or the second substrate. The supporting structure is arranged between the first substrate and the second substrate and includes a first supporting portion and a second supporting portion. A height of the first supporting portion is greater than that of the second supporting portion in a direction perpendicular to a plane where the first substrate is located. A minimum distance between the second supporting portion and the liquid-blocking portion is less than that between the first supporting portion and the liquid-blocking portion.

Abstract: Using labelled training content, a content classification model is trained. Using the trained content classification model, a label describing a first content is determined. The first content is classified into a category in a set of categories using the label. Responsive to the first content being classified into a category of inappropriate content, the first content is removed from a storage location.

Abstract: A method for contrastive learning by selecting dropout ratios and locations based on reinforcement learning includes receiving training data having a positive sample corresponding to a target and negative samples not corresponding to the target. A dropout policy for a neural network is produced based on the training data, where the dropout policy identifies at least one connection between neurons in the neural network to dropout. The training data is encoded, based on the dropout policy, to form embeddings, where the embeddings include multiple positive sample embeddings corresponding to the positive sample and multiple negative sample embedding corresponding to the negative samples.

Abstract: A display panel, a display device and a method for driving a display panel are provided. The display panel includes N types of display areas which includes an i-th type display area and a j-th type display area. The display panel includes M display parts which include a first display part and a second display part. The first display part includes at least one i-th type display area, and the second display part includes at least one i-th type display area. At least one j-th type display area is arranged between the i-th type display area included in the first display part and the i-th type display area included in the second display part. Light-emitting time periods of the i-th type display area and the j-th type display area at least partially do not overlap, to reduce the number of sub-pixels driven at the same time period.

Abstract: Techniques are described with respect to a system, method, and computer product for enhancement of socialization between one or more individuals wearing personal protective equipment. An associated method includes identifying a plurality of social communications between one or more individuals wearing personal protective equipment (PPE) and assigning an identifier to a participant associated with at least one of the social communications. The method further includes analyzing content of the at least one social communication and generating an augmented reality (AR) based representation of the content for presentation on an augmented reality device associated with the user, the augmented reality device presenting the content for visualization replacing PPE based at least in-part on the identifier.

Abstract: Methods for creating a knowledge graph for a video are disclosed. Aspects include obtaining the video, processing the video to extract audio information and video information, and storing the extracted audio information and video information with a timestamp corresponding its occurrence in the video. Aspects also include creating a plurality of groups of the extracted audio information and video information based at least in part on the timestamps and extracting two or more keywords from each of the plurality of groups. Aspects further include identifying a relationship between the two or more keywords based on the extracted audio information and video information and creating a graph having a plurality of nodes and a plurality of links that connect a pair of nodes of the plurality of nodes. Each node corresponds to an extracted keyword and each link corresponds to the identified relationship between the pair of nodes.

Abstract: An approach is provided in which the approach receives an image that includes multiple image points and constructs a plane in the image based on a first subset of the plurality of image points. The approach identifies a second subset of the image points that belong to the plane and are not part of the first subset of image points, and removes the first subset of image points and the second subset of image points form the image points. The approach annotates the remaining subset of image points in the image.

Abstract: Aspects of the subject disclosure may include, for example, detecting a plurality uplink data packets on a network, the plurality of uplink data packets conveying application protocol messages from an application on a mobile device to an application server providing a service to the application on the mobile device over the network; providing data packets of the plurality uplink data packets to a machine learning model, the machine learning model trained to identify respective application protocol messages from the data packets; receiving from the machine learning model an indication that a start video download application protocol message has been identified by the machine learning model, the start video download application protocol message requesting initiation of a video download to the application on the mobile device from the application server; detecting a plurality of downlink data packets on the network, the plurality of downlink data packets conveying video content data to the mobile device in respo

Abstract: A method for restoration of a kinetic event using video. The method includes obtaining video involving the kinetic event including a plurality of frames. An absolute location of a frame of the plurality of frames is determined. Movement of a feature point cloud corresponding to an object in motion in the plurality of frames is analyzed. A 3D object model with substantially similar dimensions to the object in motion is selected. The 3D object model is displayed emulating the analysed movement on the 3D map based on the absolute location.

Abstract: A method for detecting and labeling a target object in a 2D image includes receiving a plurality of 2D images from a visual sensor, manually marking points of the target object on each of the 2D images, generating from the 2D images a 3D world coordinate system of the environment surrounding the target object, mapping each of the marked points on the 2D images to the 3D world coordinate system using a simultaneous localization and mapping (SLAM) engine, automatically generating a 3D bounding box covering all the marked points mapped to the 3D world coordinate system, mapping the 3D bounding box to each of the 2D images, generating a label for the target object on each of the 2D images using a machine learning object detection model, and training the machine learning object detection model based on the generated label for the target object.

Abstract: Aspects of the subject disclosure may include, for example, obtaining input data, processing the input data to generate output data, the output data including an identification of one or more characteristics associated with tethered communications involving at least a first user equipment, and based on the identification of the one or more characteristics, causing an action to be taken. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of receiving a plurality of data packets captured from a network, wherein the data packets are associated with streaming video content across the network, and wherein the video content is encrypted; processing the plurality of data packets to extract features from each of the data packets in the plurality of data packets; providing the features to a trained machine learning (ML) model comprising a plurality of layers; and outputting an identification of the video content determined by the ML model. Other embodiments are disclosed.

Abstract: A method for providing a service based on a user scenario, a terminal device, and a system. The terminal device perceives the user scenario with low power consumption, and a cloud-side service open platform determines a corresponding scenario package based on the user scenario, where the scenario package includes a plurality of pre-orchestrated services for the user scenario. The service open platform pushes data related to the determined scenario package to the terminal device, and the terminal device displays entry interfaces of the plurality of services, and provides a corresponding service based on an operation performed by a user on the entry interface.

Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving encrypted hypertext transport protocol (HTTPS) traffic including media content; separating the HTTPS traffic into audio segments and video segments; calculating a size for each audio segment in the HTTPS traffic; maintaining a sliding window of a plurality of sizes of consecutive audio segments to form a fingerprint; and identifying the media content by matching the fingerprint with a reference in a catalog. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving encrypted hypertext transport protocol (HTTPS) traffic including media content; separating the HTTPS traffic into audio segments and video segments; calculating a size for each audio segment in the HTTPS traffic; maintaining a sliding window of a plurality of sizes of consecutive audio segments to form a fingerprint; and identifying the media content by matching the fingerprint with a reference in a catalog. Other embodiments are disclosed.

Abstract: A UI service loading method is applied to a loading apparatus. One example method includes: receiving a loading request including a reuse path of a to-be-loaded UI service, where the loading request requests to load the to-be-loaded UI service; determining a dependency of the to-be-loaded UI service based on a dependency graph; and loading the to-be-loaded UI service and the dependency of the to-be-loaded UI service, where the reuse path of the to-be-loaded UI service indicates an access path of the to-be-loaded UI service, and the dependency graph indicates a dependency of at least one UI service in at least one UI service package, and indicates a UI service that references a UI service in the at least one UI service package as a dependency.

Abstract: Provided is a display panel, comprising a substrate and light-emitting units on a side of the substrate; a black matrix, located on a side of the light-emitting unit way from the substrate, and provided with black matrix openings, a black matrix opening corresponds to a light-emitting unit; and a filter layer, comprising color-resistance units which are disposed in the black matrix openings and at least partially overlap with the light-emitting units of the same color in a direction perpendicular to a plane of the display panel; a color-resistance unit includes microparticles having a particle size, and a difference between the particle size and a wavelength of light emitted by a corresponding light-emitting unit is within a preset range, and the light-emitting units of different colors correspond to different particle sizes of the microparticles of the color-resistance units.

Abstract: A system, method, and computer program product provides a way to separate connected or adhered adjacent characters of a digital image for license plate recognition. As a threshold processing, the method performs a recognition of character adhesion by obtaining character parameters using an image processor. The parameters include a horizontal max crossing and a ratio of width and height. A first rule-based module is used responsive to the character parameters to distinguish the adhered characters (character adhesions) that are easy to judge, leaving the uncertain part to a character adhesion classifier model for discrimination. Character adhesion data is obtained by data augmentation including the adding of a random distance between two single characters to create class like adhered characters. Then the character adhesion classifier model of single character and character adhesion data is trained. Any uncertain part can be distinguished by the trained character adhesion classifier model.