Abstract: Anomalous events in a driving environment can be detected and/or validated by leveraging inherent human behavior. A notification of the anomalous event can be received from an initial connected entity in the driving environment. In response, an inquiry can be sent to connected entities spatiotemporally related to the initial connected entity as to whether any person associated with the connected entities is exhibiting an inherent human behavior. When a threshold level of responses to the inquiry are received from the connected entities indicating that an inherent human behavior has been detected, the one or more connected entities can be caused to upload driving scene data for at least a time when the inherent human behavior by the occupant of the connected vehicle was detected.

Abstract: A system configured to emulate a correlithm object processing system includes an input node, a first output node, and a second output node. The input node receives a real-world numeric value comprising a plurality of numerical digits, and a flag indicating a numeric system associated with the numeric value. The first output node receives a first one of the plurality of numerical digits and generates a first correlithm object associated with the first numerical digit. The second output node receives a second one of the plurality of numerical digits and generates a second correlithm object associated with the second numerical digit. A string correlithm object engine maps the first correlithm object to a first sub-string correlithm object of a string correlithm object, and maps the second correlithm object to a second sub-string correlithm object of the string correlithm object.

Abstract: Example embodiments of the present disclosure provide an image detection method, an electronic device and a computer-readable storage medium. The image detection method includes the following. Am image to be detected including a target object is obtained and multiple feature representation determination modules are obtained. The multiple feature representation determination modules are trained for different parts of a reference object, using a reference image including the reference object and an authenticity of the reference image. Multiple feature representations for different parts of the target object are determined based on the image to be detected and the multiple feature representation determination modules. An authenticity of the image to be detected is determined based on the multiple feature representations.

Abstract: A technology capable of dealing with a variation in appropriate recognition parameters due to a change in work environment at a work site at a time of recognizing an article in an image. An article recognition system includes: an input section to which a captured image is input; an output section that presents information to a user; a storage section that stores master data defining features of an object to be recognized; a recognition section that detects the object to be recognized in the image; and a recognition evaluation section that evaluates a recognition content of the recognition section and that presents an alert to the output section on the basis of an evaluation result.

Abstract: Wireless communications systems and methods related to mitigating maximum permissible exposure (MPE) constraints based on user equipment (UE) feedback are provided. A first wireless communication device transmits, to a second wireless communication device, a plurality of reports, each report indicating an allowable transmission power level at the first wireless communication device satisfying an MPE parameter. The first wireless communication device receives, from the second wireless communication device, a first configuration based on an MPE profile associated with the first wireless communication device in response to the plurality of reports. The first wireless communication device transmits, to the second wireless communication device, a first communication signal over a first beam based on the first configuration.

Abstract: An image feature extraction method for person re-identification includes performing person re-identification by means of aligned local descriptor extraction and graded global feature extraction; performing the aligned local descriptor extraction by processing an original image by affine transformation and performing a summation pooling operation on image block features of same regions to obtain an aligned local descriptor; reserving spatial information between inner blocks of the image for the aligned local descriptor; and performing the graded global feature extraction by grading a positioned pedestrian region block and solving a corresponding feature mean value to obtain a global feature. The method can resolve the problem of feature misalignment caused by posture changes of pedestrian, etc., and eliminate the effect of unrelated backgrounds on re-recognition, thus improving the precision and robustness of person re-identification.

Abstract: Embodiments described herein provide a two-stage online detection of action start system including a classification module and a localization module. The classification module generates a set of action scores corresponding to a first video frame from the video, based on the first video frame and video frames before the first video frames in the video. Each action score indicating a respective probability that the first video frame contains a respective action class. The localization module is coupled to the classification module for receiving the set of action scores from the classification module and generating an action-agnostic start probability that the first video frame contains an action start.

Abstract: Methods and apparatus for determining poses of objects acquire plural images of the objects from different points of view. The images may be obtained by plural cameras arranged in a planar array. Each image may be processed to identify features such as contours of objects. The images may be projected onto different depth planes to yield depth plane images. The depth plane images for each depth plane may be compared to identify features lying in the depth plane. A pattern matching algorithm may be performed on the features lying in the depth plane to determine the poses of one or more of the objects. The described apparatus and methods may be applied in bin-picking and other applications.

Abstract: The present invention relates to a method for controlling a device controller of an electronic device comprising a fingerprint sensor to transition from an at least partly active mode to an at least partly in-active mode. The fingerprint sensor itself is used for determining a presence of a finger on the fingerprint sensor, wherein a device controller is maintained in an at least partly active mode if a finger is detected on the fingerprint sensor. The present invention also relates to an electronic device comprising a fingerprint sensor and a device controller.

Abstract: A method, computer program, and computer system is provided for estimating three-dimensional hand poses in images. Data corresponding to two hand images is receive, and an optical flow value corresponding to a change in a hand gesture in the received hand image data is calculate. A heat map is generated based on the calculated optical flow, and a hand mesh map is estimated based on the generated heat map. A hand pose present within the hand images is determined based on the estimated hand mesh map.

Abstract: Aspects of the disclosure relate to detecting an emergency vehicle. For instance, a plurality of images may be taken from a perspective of an autonomous vehicle. One or more gates representing a region of interest at a respective distance from the vehicle may be generated for the images. A plurality of lights may be detected within the one or more gates. A first candidate emergency vehicle may be identified from a detected plurality of lights in one or more gates of one of the images, and a second candidate emergency vehicle may be identified from a detected plurality of lights in one or more gates of another of the images. The first and second candidate emergency vehicles are determined to be the same emergency vehicle and to be active. An operational system of the autonomous vehicle is controlled based on the determination that the given emergency vehicle is active.

Abstract: Methods, systems, and devices for wireless communication are described. A user equipment (UE) may report a phase-noise compensation reference signal (PCRS) configuration to a base station to enable per-UE PCRS signaling. For example, a UE may operate in a wireless communications system using carrier frequencies greater than 6 GHz, which may be affected by phase noise. The UE may accordingly determine a PCRS configuration based on a capability to receive signals. The PCRS configuration may include a resource mapping for one or more PCRS, a number of PCRS ports used for PCRS, a multiplexing scheme for one or more PCRS ports, or the UE's phase noise estimation capability. The UE may then transmit a reporting message including the PCRS configuration to a base station. The base station may use the PCRS configuration for PCRS transmissions to the UE.

Abstract: A light emitting device includes a wiring substrate, a light emitting element array that includes a first side surface and a second side surface facing each other, and a third side surface and a fourth side surface connecting the first side surface and the second side surface to each other and facing each other, the light emitting element array being provided on the wiring substrate, a driving element that is provided on the wiring substrate on the first side surface side and drives the light emitting element array, a first circuit element and a second circuit element that are provided on the wiring substrate on the second side surface side to be arranged in a direction along the second side surface, and a wiring member that is provided on the third side surface side and the fourth side surface side and extends from a top electrode of the light emitting element array toward an outside of the light emitting element array.

Abstract: A system includes a controller communicatively coupled to an optical inspection sub-system, the controller configured to: receive training images of a sample; identify alignment targets in the master die; receive a first set of reference images of a first die row of a sample, the first die row including a master die and a first set of reference die; align the first set of reference die to the master die via fine alignment processes to generate a first set of aligned reference images of the first row; receive a second set of reference images of a second die row of the sample; align the second set of reference die to the master die based on the alignment targets and the training images using a course alignment offset value; and align the second set of reference die to the master die via a fine alignment process.

Abstract: A method includes obtaining, using first and second image sensors of an electronic device, first and second images, respectively, of a scene. The method also includes obtaining, using an image depth sensor of the electronic device, a third image and a first depth map of the scene, the first depth map having a resolution lower than a resolution of the first and second images. The method further includes undistorting the first and second images using the third image and the first depth map. The method also includes rectifying the first and second images using the third image and the first depth map. The method further includes generating a disparity map using the first and second images that have been undistorted and rectified. In addition, the method includes generating a second depth map using the disparity map and the first depth map, where the second depth map has a resolution that is higher than the resolution of the first depth map.

Abstract: Systems and methods to configure sidelink resources in a dual connectivity operation are provided. In some aspect, a method comprising: transmitting, from a user equipment (UE), a first message to a first evolved Node B (eNB), wherein the first message indicates a request to establish a sidelink communication; receiving, at the UE, a second message from the first eNB, wherein the second message indicates a frequency that is used by a secondary evolved Node B (SeNB); transmitting, from the UE, a measurement result to the first eNB; and receiving, at the UE, sidelink configuration information from the first eNB, wherein the sidelink configuration information indicates sidelink resources managed by the secondary eNB.

Abstract: Automated determination of muscle mass from images can be carried by performing a thresholding process to an image file to generate a contrasted image, and segmenting pixels of the contrasted image into bone and not bone. The system can distinguish muscle from organ for the pixels segmented as not bone by determining a location of a rib cage of the patient using the pixels segmented as bone, and removing pixels segmented as not bone that are located within the location of the rib cage. The system can calculate a volume of muscle based on remaining pixels segmented as not bone; calculate a total muscle mass based on the volume of muscle; and provide the total muscle mass of the patient. The total muscle mass of the patient can then be used for applications including calculating a glomerular filtration rate.

Abstract: Provided are an artificial intelligence (AI) system for simulating functions such as recognition, determination, and so forth of the human brain by using a mechanical learning algorithm like deep learning, or the like, and an application thereof.

Abstract: An object detection device calculates, for each of images acquired in time-series, a confidence score of each of a plurality of types of an object to be detected for each of a plurality of regions on the image, detects the type of the object corresponding to the confidence score in a region in which the confidence score is equal to or higher than a confidence threshold of the type for each of the images, tracks the detected object, counts a frequency of occurrence for each type of the detected object in a period in which the detected object is tracked, and updates the confidence threshold in such a way that the confidence threshold of a type having a higher frequency of occurrence is lower than the confidence threshold of a type having a lower frequency of occurrence.

Abstract: A system, method, and computer program product for tracking interactive events. Facial expression data and interactive event data are received. A new facial expression is detected in the facial expression data, and the new facial expression and corresponding interactive event data are recorded. The new facial expression is recognized based on training data, and in response, a definition is assigned to the new facial expression. The corresponding interactive event data is tagged with the definition.