Abstract: A method for training a classifier for image data using learning image data and associated labels, each of the labels including an allocation to one or multiple classes of a predefined classification. In the method, for each data set of learning image data, space-resolved relevance maps are provided, which indicate how relevant which spatial areas of the particular learning image data are for the assessment of the situation shown in the learning image data. From data sets of learning image data and associated relevance maps, learning samples are ascertained; the learning samples are fed to the classifier; and classifier parameters are optimized with the aim that the classifier maps the learning samples to allocations to one or multiple classes which are consistent with the labels of the learning image data from which the learning samples originate.

Abstract: A method and apparatus for handling dynamic group creation in a vehicle to everything (V2X) system is provided. The method includes assigning, by a first server, a link layer identifier corresponding to a dynamic group information, sending, by the first server, a push request including the link layer identifier corresponding to the dynamic group information to a first V2X user equipment (UE) from a plurality of V2X UEs, receiving, by the first V2X UE, the link layer identifier corresponding to the dynamic group information, storing, by the first V2X UE, the link layer identifier corresponding to the dynamic group information.

Abstract: Systems, methods, and storage media for automatically identifying skin conditions based on images and other data using machine learning methods and algorithms that encode expert knowledge of skin conditions. The systems, methods, and storage media may also leverage infrastructure that facilitates the collection, storage, labeling, dynamic organization, and expert review of existing and incoming data.

Abstract: An information processing apparatus (2) includes: an extracting unit (212) that extracts a key point (KP) of a target object as a target key point (KP1) from an input image (IMG1); and a calculating unit (213) that calculates, as a score (SC) of the input image from which the target key point is extracted, an index value related to a reliability of the target key point based on the target key point.

Abstract: An antenna module includes a first antenna unit including at least one first patch antenna pattern, at least one first feed via, and at least one first dielectric layer, a second antenna unit including at least one second patch antenna pattern, at least one second feed via, and at least one second dielectric layer, a first connection portion, a first rigid substrate electrically connecting the first connection portion to the first antenna unit and having a first surface on which the first antenna unit is disposed, a base connection portion, a flexible substrate having a first surface on which the first connection portion is disposed and a second surface on which the base connection portion is disposed, and an IC electrically connected to the flexible substrate through the second surface of the flexible substrate or the first rigid substrate.

Abstract: An automated driving system includes an object detection system. A neural network image encoder generates image embeddings associated with an image including an object. A neural network text encoder generates concept embeddings associated with each of a plurality of concepts. Each of the plurality of concepts is associated with one of at least two object classes. A confidence score module generates a confidence score for each of the plurality of concepts based on the image embeddings and the concept embeddings associated with the concept. An object class prediction module generates a predicted object class of the object based on an association between a set of concepts of the plurality of concepts having at least two of the highest values of the generated confidence scores and the one of the at least two object classes associated with a majority of the set of concepts.

Abstract: A time series of face images of a human during a human activity are captured. A first artificial neural network (ANN) processing pipeline processes the captured time series of face images to provide a first attention level indicator signal. An electrophysiological signal indicative of the level of attention of the human during the activity is also captured. A second ANN processing pipeline processes the sensed electrophysiological signal to providing a second attention level indicator signal. A risk indicator signal is then generated based on at least one of the first attention level indicator and second attention level indicator. A user circuit is then triggered as a result of the risk indicator reaching or failing to reach at least one attention level threshold.

Abstract: Method and system for determining the angle of anteversion of for example bone fragments of a fractured bone are disclosed. Supported by artificial intelligence, a first object is classified in a first X-ray projection image. A second object is classified in a second X-ray projection image. A spatial arrangement of the objects relative to each other can be determined based on a respective determination of a representation and a localization of both objects.

Abstract: Systems, methods, and storage media for automatically identifying medical conditions based on images and other data using machine learning methods and algorithms that encode expert knowledge of medical conditions. The systems, methods, and storage media may also leverage infrastructure that facilitates the collection, storage, labeling, dynamic organization, and expert review of existing and incoming data.

Abstract: A large-scale radio frequency signal information processing and analysis system that provides advanced signal analysis for telecommunication applications, including band capacity and geographical density determinations and detection, classification, identification, and geolocation of signals across a wide range of frequencies and across broad geographical areas. The system may utilize a range of novel algorithms for bin-wise processing, Rayleigh distribution analysis, telecommunication signal classification, receiver anomaly detection, transmitter density estimation, transmitter detection and location, geolocation analysis, telecommunication activity estimation, telecommunication utilization estimation, frequency utilization estimation, and data interpolation.

Abstract: An embodiment of the present disclosure provides a method for a first apparatus for transmitting a groupcast service. The method comprises the steps of: determining, based on a plurality of unicast services received from a plurality of apparatuses, mapping information indicating the mapping relationship between the plurality of unicast services and a groupcast service; and transmitting, based on the mapping information, the groupcast service to a second apparatus and a third apparatus included in the plurality of apparatuses.

Abstract: A communication system includes a communication apparatus and a communication terminal configured to wirelessly communicate with each other, wherein the communication terminal includes a first wireless communication interface configured to support a Bluetooth® standard and include a single antenna, and wherein the communication apparatus includes a second wireless communication interface configured to support the Bluetooth® standard and include a plurality of antennas, and includes one or more controllers configured to function as a unit configured to obtain angle information and field intensity information based on a result of reception of radio waves, by the plurality of antennas, transmitted from the single antenna; and a unit configured to transmit an establishment request for wireless communication based on the Bluetooth® standard to the first wireless communication interface via the second wireless communication interface based on a fact that the angle information and the field intensity information sat

Abstract: The disclosed method and an apparatus are directed to determine an uplink transmission power in in New Radio (NR) systems by a wireless transmit/receive unit (WTRU) for transmitting at least one physical uplink shared channel (PUSCH), using multiple beams toward multiple Tx/Rx points (TRPs). The method includes determining common parameters like a target receive power, a modulation and coding scheme (MCS) specific offset, and a transmit power control (TPC) command parameters common to the multiple beams. The method also includes determining beam-specific parameters like path loss for each beam, a configurable fractional power compensation factor for each beam, and a configurable maximum transmit power level of the each beam, wherein the fractional power compensation factor and the configurable maximum transmit power level for the each beam are determined dynamically or semi-statically based on at least deployment, WTRU mobility, or interference level.

Abstract: Embodiments of the disclosure include a method, a device, and a computer program product for video processing. This method includes: selecting frames having features of a first type from a first instance of a video as a first candidate set, the first instance having a first resolution; generating a set of training frames based at least on the first candidate set; acquiring a set of corresponding frames for the set of training frames in a second instance of the video, the second instance having a second resolution lower than the first resolution; and determining, using the set of training frames and the set of corresponding frames, a conversion parameter for conversion from the second resolution to a third resolution. This solution provides a smaller-scale and higher-quality training set for the training of a video conversion model, thus improving the quality of training while saving computational resources and increasing training speed.

Abstract: An apparatus for providing brain lesion information based on an image includes a magnetic resonance angiography (MRA) provider configured to provide an environment capable of displaying 3D time-of-flight magnetic resonance angiography (3D TOF MRA) using user input, a brain lesion input unit configured to generate and manage a brain lesion image, a maximum intensity projection (MIP) converter configured to configure MIP image data including at least one image frame corresponding to a projection position of the brain lesion image, a noise remover configured to remove noise of brain lesion information and to configure corrected MIP image data, from which the noise is removed, and an MRA reconfiguration unit configured to reconfigure a corrected brain lesion image by back-projecting the corrected MIP image data.

Abstract: An image processing apparatus includes: a receiving unit configured to receive registration of a new image group for at least one existing image group; and a generation unit configured to specify an image having consistency with representative images, which are set for the existing image groups respectively, out of the images included in the new image group, and generate from the specified image a representative image of the new image group.

Abstract: Reducing the number of parameters in a visual parameter set based on a sensitivity analysis of how a given visual parameter affects the performance of a computer vision model to provide a verification parameter set having a reduced size.

Abstract: An apparatus includes at least one camera configured to capture a series of image frames for traffic lanes in front of an ego vehicle, where each of the series of image frames is captured at a different one of a plurality of times. A target object detection and tracking controller is configured to process each of the image frames using pixel measurements extracted from the respective image frame to determine, from the pixel measurements, a predicted time to line crossing for a target vehicle detected in the respective image frame at a time corresponding to capture of the respective image frame.

Abstract: Method for estimating a vertical offset of road segment for vehicle is disclosed. The method includes tracking road reference on road segment at first moment in time from first observation point in order to form first representation. Method includes obtaining vehicle movement data over time period extending from first moment in time to second moment in time, tracking road reference on road segment at second moment in time from second observation point in order to form second representation.

Abstract: A margin assessment method is provided. Under cooperation of harmonic generation microscopy (HGM) and a deep learning method, the margin assessment method can instantaneously and digitally determine whether a 3D image group generated by an HGM imaging system is a malignant tumor or the surrounding normal skin, so as to assist in determining margins of a lesion.