Abstract: An example communication system includes remote units to exchange radio frequency (RF) signals with mobile devices, RF signals comprising information destined for, or originating from, a mobile device, the remote units performing at least some physical layer processing for an air interface used by the remote units to communicate with the mobile device. The communication system also includes two or more controllers comprising real-time schedulers for assigning airlink resources to the mobile device for the information. The communication system also includes a coordination function coupled to the two or more controllers to coordinate assignments made by the real-time schedulers in the two or more controllers.

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: An online concierge system trains a classification model as a domain adversarial neural network from training data labeled with source classes from a source domain that do not overlap with target classes from a target domain output by the classification model. The online concierge system maps one or more source classes to a target class. The classification model extracts features from an image, classifies whether an image is from the source domain or the target domain, and predicts a target class for an image from the extracted features. The classification model includes a gradient reversal layer between feature extraction layers and the domain classifier that is used during training, so the feature extraction layers extract domain invariant features from an image.

Abstract: Systems, and method and computer readable media that store instructions for high-resolution face recognition.

Abstract: Tomographic images acquired by iterative reconstruction of low quality projection images, are enhanced by the steps of correcting at an iteration step the result of the previous iteration step by means of a back-projection of the result of a comparison of a projection image and the forward projection of the result of the previous iteration step whereby this result is enhanced by subjecting it to a trained neural network.

Abstract: The embodiments of the present disclosure provide a method of registering a face based on video data, including: receiving video data; acquiring a first image frame sequence from the video data, wherein each image frame in the first image frame sequence includes a face detection frame containing a complete facial feature; determining whether each image frame reaches a preset definition or not according to a relative position of the face detection frame in the image frame; extracting a plurality of sets of facial features based on an image information of the plurality of face detection frames in response to determining that the image frame reaches the preset definition, and determining whether the faces represent an object or not according to the plurality of sets of facial features; and registering the object according to the first image frame sequence in response to determining that the faces represent the object.

Abstract: This application provides a data transmission method and related apparatus. The data transmission method is applied to a communications system. An access point in the communications system includes a first communications apparatus and a second communications apparatus, and a station in the communications system includes a third communications apparatus and a fourth communications apparatus. The data transmission method includes that after failing to send a first data frame to the third communications apparatus through a first channel, the first communications apparatus retransmits the first data frame, and sends a same second data frame to the second communications apparatus. The first communications apparatus receives a first notification message sent by the second communications apparatus. The first communications apparatus stops, in response to the first notification message, sending the first data frame.

Abstract: According to a method for pushing a notification provided in some embodiments of the present disclosure, a to-be-notified event is obtained; a first notification condition and a second notification condition are determined; a first notification page is displayed on the display when the first notification condition is met, to display, to a user, first association information when the first notification condition is met, for example, event status information, to-be-executed behavior information, and operation association information; and a second notification page is displayed on the display when the second notification condition is met after the first notification page is displayed, to display, to the user, second association information when the second notification condition is met. A plurality of notification pages are pushed for a to-be-notified event, and each notification page is pushed when a notification condition is met as the event develops.

Abstract: A method of biometric identification of a person comprises, during an enrolment phase determining at least one enrolment transfer function for bone conduction of an audio signal through an enrolling user's head. The enrolment transfer function is stored. During a verification phase, at least one verification transfer function for bone conduction of an audio signal through the person's head is determined. It is then determined from the at least one verification transfer function and the at least one enrolment transfer function whether the person is the enrolling user.

Abstract: Systems and methods for generating thin slice images from thick slice images are disclosed herein. In some examples, a deep learning system may calculate a residual from a thick slice image and add the residual to the thick slice image to generate a thin slice image. In some examples, the deep learning system includes a neural network. In some examples, the neural network may include one or more levels, where one or more of the levels include one or more blocks. In some examples, each level includes a convolution block and a non-linear activation function block. The levels of the neural network may be in a cascaded arrangement in some examples.

Abstract: The invention provides a method and device for protecting a child inside a vehicle, a computer device, a computer-readable storage medium, and a vehicle, which are applied to the technical field of automobiles. The method for protecting a child inside a vehicle includes: receiving image data inside a vehicle; performing facial detection on the image data to detect passengers in the vehicle; further classifying the detected passengers in the vehicle into children and adults according to the facial detection; and performing a corresponding protection operation when a result of the classification indicates that there is a child alone in the vehicle.

Abstract: The present application relates to the field of data processing, and provides a method for deploying a face sample library, and a method and an apparatus for business processing based on face recognition. The method for deploying a face sample library, comprises: obtaining historical business information of users corresponding to face samples in a password face sample library under a condition that a number of face samples in the password face sample library is greater than or equal to a preset sample number threshold, wherein confidential business passwords of the users corresponding to the face samples in the same password face sample library are the same; dividing the password face sample library to obtain M levels of face sample sub-libraries according to the historical business information, where M is a positive integer. Use of the technical solution of the present application improves the accuracy of business processing using face recognition.

Abstract: An image processing device includes a receiver configured to receive a plurality of images of a subject from a camera; and a processor configured to: calculate, for each of the plurality of images, an angle difference between a gaze angle and a head angle of the subject to obtain a series of angle differences; and determine an authenticity of the subject at least based on the series of angle differences.

Abstract: According to some embodiments, an imaging processing method for extracting a plurality of planar surfaces from a depth map includes computing a depth change indication map (DCI) from a depth map in accordance with a smoothness threshold. The imaging processing method further includes recursively extracting a plurality of planar region from the depth map, wherein the size of each planar region is dynamically adjusted according to the DCI. The imaging processing method further includes clustering the extracted planar regions into a plurality of groups in accordance with a distance function; and growing each group to generate pixel-wise segmentation results and inlier points statistics simultaneously.

Abstract: A face liveness detection method is performed by an electronic device. The method includes: obtaining an initial face image of an object and a face image set of the object captured at N different illumination directions; obtaining N difference images according to the initial face image and the N face images in the face image set; generating a normal map and an albedo map according to the N difference images and the N illumination directions; and determining a face liveness detection result according to the N difference images, the normal map, and the albedo map, the face liveness detection result indicating whether the object has a live face or not. In this application, three-dimensional (3D) geometric information and surface material information of a face image are considered, thereby recognizing the authenticity of the face image, and effectively resisting different face liveness attack manners.

Abstract: Systems, apparatuses, and methods related to comparison of biometric identifiers in memory are described. An example apparatus includes an array of memory cells, a plurality of logic blocks in complementary metal-oxide-semiconductor (CMOS) under the array, and a controller coupled to the array of memory cells. The controller is configured to control a first portion of the plurality of logic blocks to receive a first subset of a set of biometric identifiers from the array and to perform a first comparison operation thereon and control a second portion of the logic blocks to receive a second subset of the set of biometric identifiers from the array and to perform a second comparison operation thereon. The first and second subsets of the biometric identifiers are different biometric identifiers and the first and second comparison operations are performed to determine a match of the first and second subsets respectively to a stored template.

Abstract: Provided are a face-hand correlation degree detection method and apparatus, a device, and a storage medium. The method includes that: an image to be detected is acquired; a face feature set and a hand feature set of the image to be detected are determined on the basis of a result obtained by performing face and hand detection on the image to be detected; a first interaction feature of a target face is determined on the basis of a face feature of the target face and the hand feature set; a second interaction feature of a target hand is determined on the basis of a hand feature of the target hand and the face feature set; and a correlation between the target face and the target hand is determined on the basis of the first interaction feature and the second interaction feature.

Abstract: Systems and methods for detecting a potential object for a powered door of a vehicle. The system includes an electronic control unit and a noncontact sensor, the noncontact sensor having a field-of-view substantially including an obstacle detection zone defined for a powered door. The electronic control unit is configured to receive data from the noncontact sensor, determine, based on the data received from the noncontact sensor, an object located at a position within the field-of-view of the noncontact sensor, determine whether the position of the object is within the obstacle detection zone defined for the powered door, and in response to the position of the object being within the obstacle detection zone for the powered door, perform an automatic action with respect to the powered door before the powered door contacts the object.

Abstract: A three-dimensional sensor generates multiple items of line data with respect to multiple horizontal lines arranged at different heights. Multiple first neural networks each generate first intermediate data relating to a corresponding item from among the multiple items of line data. Each first intermediate data indicates the probability of matching between the corresponding line data and each of multiple portions of multiple kinds. A combining processing unit receives the multiple items of first intermediate data, and combines the first intermediate data thus received so as to generate at least one item of second intermediate data. A second neural network receives the at least one item of second intermediate data, and generates final data that indicates the probability of matching between the object and each of the multiple kinds.

Abstract: An image processing apparatus includes a detector, a grouping processor, a management unit, and a determination unit. The detector detects traffic signals on the basis of a captured image. The grouping processor performs a grouping process of causing each of the detected traffic signals to belong to any one of groups. The management unit manages a location and display information of the each of the detected traffic signals in association with the group to which the each of the traffic signals belongs, and thereby manages the traffic signals. The determination unit determines, for each of the groups, a representative location and representative display information of one or more traffic signals belonging to relevant one of the groups, among the traffic signals, on the basis of the location and display information of each of the one or more traffic signals belonging to the relevant one of the groups.