Abstract: Systems, devices, methods, instructions stored on media, and other embodiments for a camera interface are described. A standardized modular camera interface may be presented with context elements based on a target interface used to initiate presentation of the camera interface, and with customized actions for creating and sending content, as well as returning to the target interface. In some embodiments, the camera interface includes an audio quality feedback element that is displayed while content is being captured. Such an element can provide feedback on audio quality as the content is being captured. In various embodiments, shape or color displays and changes indicate varying audio quality conditions. Such indicators are, in some embodiments, generated by processing audio stream segments in a machine learning model to generate an audio quality score used to generate the feedback element.

Abstract: The disclosed technology provides solutions for implementing dynamic autonomous vehicle (AV) dispatch services. A process of the disclosed technology can include steps for receiving a dispatch request from a mobile device associated with a user, wherein the dispatch request comprises a first pick-up location associated with the user, dispatching a first autonomous vehicle (AV) to the first pick-up location in response to the dispatch request, and automatically receiving an updated location of the mobile device associated with the user. In some aspects, the process can further include steps for determining a second pick-up location based on a change between the first pick-up location and the updated location, and transmitting an updated dispatch request based on the updated location of the mobile device. Systems and machine-readable media are also provided.

Abstract: One or more service data feeds that indicate a plurality of consumer eSIM profiles received are loaded into one or more profile data stores of at least one subscription management service are received at an Embedded Subscriber Identity Module (eSIM) profile management platform of a wireless communication carrier. A request from an entity to perform an action with respect to a particular consumer eSIM profile having a specific Integrated Circuit Card identifier (ICCID) may be received at the eSIM profile management platform. A request for performing the action with respect to the particular consumer eSIM profile is forwarded by the eSIM profile management platform to a subscription management service at least in response to determining that the specific ICCID matches an ICCID of a consumer eSIM profile that is indicated by the service data feed as being loaded into the profile data store of the subscription management service.

Abstract: Position information estimation in a distributed radio frequency (RF) communications system is provided. Embodiments disclosed herein facilitate high-precision estimations of positions, orientations, velocities, and acceleration of network nodes in a distributed RF network. The distributed RF communications system incorporates a series of estimation processes which makes it susceptible to propagation of errors. To ensure robustness of the distributed RF communications system, relative positions of network nodes are tracked by iteratively tracking parameters used for estimating position information. Some embodiments take advantage of Kalman filtering algorithms by leveraging principles directed by physics. At every network node, several filtering algorithms can be employed to synchronize clocks, track delay between multiple-input multiple-output (MIMO) antennas and estimate position and orientation of other network nodes.

Abstract: Methods and systems for an online charging system to grant resources to a session with a terminal device when the session includes a large file or the session has a long duration. Embodiments the invention include methods performed by an electronic device for online charging in a wireless network. In one embodiment, the electronic device receives a request message for resources to set up a session with a terminal device, where the request message is sent from a core network interface to an online charging function (OCF), and where the request message indicates that the session includes a large file or that the session has a long duration. The electronic device determines that the terminal device has enough credit for the session based on the request message and grants the resources for the session with the terminal device based on the determination.

Abstract: Provided is a first motion vector detection unit that detects a motion vector on a basis of self-motion data and depth image data. A second motion vector detection unit that detects a motion vector on a basis of captured image data. A motion vector merging unit that merges the motion vector detected by the first motion vector detection unit with the motion vector detected by the second motion vector detection unit.

Abstract: A central routing function (CRF) platform. The CRF platform comprises at least one processor; a non-transitory memory communicatively coupled to the at least one processor that stores a plurality of prioritized international call route lists where each prioritized international call route list associates alternative international communication service carrier routes in a prioritized order with an international telephone number; and a call process application stored in the non-transitory memory that, when executed by the processor, receives a request for a prioritized international call route list from a network element, where the request comprises an international telephone number, pads out the international telephone number received from the network element to form a 15-digit number, looks up a prioritized international route list using the 15-digit number in the non-transitory memory, and sends the prioritized international route list to the network element.

Abstract: A computer-implemented method is for artifact correction during a reconstruction of at least one slice image from at least one projection image. The at least one projection image includes a plurality of pixels, each pixel including a pixel value. The method includes determining at least one corrected projection image based on the at least one projection image via a computing circuit; reconstructing the at least one slice image based on the at least one corrected projection image; and providing the at least one slice image. The determining includes determining an average pixel value in at least one subarea of the at least one projection image, a correction value by multiplying the average pixel value by a scatter factor, and a plurality of corrected pixel values by subtracting the correction value from the plurality of pixel values. The corrected projection image includes pixels including the plurality of corrected pixel values.

Abstract: The invention concerns a device for identifying a clothing family index (Clo), the index in particular representing the type and level of clothing of a passenger of a motor vehicle, comprising: —at least one camera (2) designed to capture at least one image of a part of the clothing of the passenger (P), —a processing unit (3) designed to determine at least one clothing family index (Clo) by using a recognition algorithm based on a neural network model, trained in particular on a library (5) of representative images captured by the camera, images preferably categorised beforehand by a human operator.

Abstract: Certain aspects of the present disclosure provide techniques for a method of displaying a user interface on a mobile device, comprising: receiving a transaction file; performing text recognition on the transaction file to extract one or more transaction elements; determining a transaction characteristic based on the one or more transaction elements; displaying a transaction characteristic user interface element within an interactive cell displayed in the user interface; receiving a user touch gesture associated with the interactive cell via the user interface; and displaying an action user interface element in response to receiving the user touch gesture, wherein the action user interface element is configured to perform an action based on the transaction characteristic associated with the interactive cell.

Abstract: Systems and methods for generating a road map are provided. The methods include obtaining a navigation route for a navigation terminal and a current location of the navigation terminal. The methods further include obtaining road network data associated with the current location of the navigation terminal based on the navigation route and the current location of the navigation terminal. The road network data includes a plurality of links and a plurality of nodes. Each node is connected to one or more links including at least one type of links. The methods further include determining a level for each node. The methods further include determining one or more target links for the at least one type of links connected to the node based on the level of the node. The methods further include generating a road map based on the target links.

Abstract: Embodiments of the present disclosure provide a method and system for co-operative and cascaded inference on the edge device using an integrated Deep Learning (DL) model for object detection and localization, which comprises a strong classifier trained on largely available datasets and a weak localizer trained on scarcely available datasets, and work in coordination to first detect object (fire) in every input frame using the classifier, and then trigger a localizer only for the frames that are classified as fire frames. The classifier and the localizer of the integrated DL model are jointly trained using Multitask Learning approach. Works in literature hardly address the technical challenge of embedding such integrated DL model to be deployed on edge devices. The method provides an optimal hardware software partitioning approach for components or segments of the integrated DL model which achieves a tradeoff between latency and accuracy in object classification and localization.

Abstract: Disclosed is an image processing apparatus and a method of operating the same. The image processing apparatus includes: a memory storing information on at least one random patch; and at least one processor configured to: obtain correlations between a pixel block included in an input image and each of a plurality of random patches obtained from the information on the at least one random patch, obtain weights respectively for the plurality of random patches on a basis of the obtained correlations and apply the weights respectively to the plurality of random patches, and obtain an output image by applying, to the pixel block, the plurality of random patches to which the weights are respectively applied.

Abstract: Cross-service usage is dynamically enforced for different network-based services. A cross-service control system may accept requests to specify a usage quota for a client for an interface of a network-based service. A rule to enforce the usage quota may be distributed to request handling nodes for the service. Usage measurements may be collected from the request handling nodes for requests received from the client via the interface. An update to the usage quota may be determined from an evaluation of the usage measurements. The rule at the request handling nodes may be updated to enforce the updated usage quota.

Abstract: A network device executes an account management function that pre-authorizes network service unit consumption by multiple subscribers that are members of a same, shared network service account. The account management function receives, from multiple charging systems distributed within the network, network unit consumption charges associated with each of the multiple subscribers, where the network device is centrally located within a network relative to multiple locations associated with the plurality of charging systems. The account management function updates a consumption counter for the same, shared network service account based on the network unit consumption charges associated with the multiple subscribers received from the multiple charging systems distributed within the network.

Abstract: An iris scanning device that includes a single camera sensor utilized for generating iris scan data is described herein. The iris scanning device includes a selector, a lens, and the camera sensor. The selector is configured to receive a first optical signal representative of a first eye and a second optical signal representative of a second eye. The selector selectively allows a passed optical signal to be optically propagated to the lens and inhibits a blocked optical signal from being optically propagated to the lens during a time period. The passed optical signal is one of the first optical signal or the second optical signal during the time period. The blocked optical signal is a differing one of the first optical signal or the second optical signal during the time period. The lens causes the passed optical signal to be incident on the camera sensor during the time period.

Abstract: A device and a method and a non-transitory readable storage medium, for face recognition are provided, the method comprise: extracting a face sample image from a predetermined face sample library and performing feature point detection to obtain multiple face feature points; obtaining multiple mask images; selecting first to fourth face feature points from the multiple face feature points; defining a distance between the first and second face feature point as a mask image height, and defining a distance between the third and fourth face feature point as a mask image width; adjusting a size of each mask image according to the mask image height and the mask image width; fusing each adjusted mask image with the face sample image to obtain multiple face mask images to save into the predetermined face sample library; training a face recognition model based on the predetermined face sample library for face recognition.

Abstract: There are provided measures for coordinated session charging in roaming scenarios. Such measures (of a first session management entity of a first mobile network in a roaming charging related scenario between said first mobile network and a second mobile network) exemplarily comprise transmitting a session creation request message to a second session management entity of said second mobile network, said session creation request message including information indicative of a first configuration utilized for mobile network related charging, and receiving a session creation response message from said second session management entity of said second mobile network, said session creation response message including information indicative of a second configuration utilized for mobile network related charging.

Abstract: Provided is a human posture detection method including: acquiring a plurality of frames of image data; acquiring a plurality of human posture reference maps output by a human posture detection model responsive to inputting a current frame of image data to the human posture detection model with reference to human posture confidence maps of a previous frame of image data, wherein different human posture reference maps correspond different human-posture key points; identifying a human-posture key point in each of the human posture reference maps; and generating human posture confidence maps of the current frame of image data based on credibility of the human-posture key points, wherein the human posture confidence maps of the current frame of image data is configured to participate in generation of human posture confidence maps of a next frame of image data.

Abstract: A method may include obtaining a plurality of training samples with a plurality of classifications that include a first classification and a second classification, training an initial tree with an initial set of training samples selected from the plurality of training samples using an initial set of feature values extracted from the set of training samples, and, in response to determining that the initial tree incorrectly classified the initial set of training samples at an output node of the initial tree, training a subsequent tree using a subsequent set of feature values extracted from a subsequent set of training samples.