Abstract: A correlation value calculation device for calculating a correlation value between a base block within an image and at least one reference block within the image or other image includes a pixel value distribution calculation unit configured to calculate a pixel value distribution of pixels within the image and select a range of pixel values of a large number of pixels as a valid pixel value range, a conversion coefficient calculation unit configured to calculate conversion coefficients for converting pixels of the valid pixel value range into a prescribed bit-depth, and a pixel value conversion unit configured to perform a bit-depth reduction process on pixels within the base block and pixels within the reference block on the basis of the conversion coefficients.

Abstract: Systems and methods for dynamically maintaining and utilizing walking profiles for time estimations in service scheduling are provided. A networked system detects usage of an application on a user device. In response to the detecting, the networked system accesses environmental condition data at a location associated with a user of the user device, whereby the environmental condition data comprises one or more environmental condition affecting the location. The networked system accesses walking pace data from the user device, whereby the walking pace data represents a current walking pace of the user and correlates the walking pace data with the environmental condition data. Using the correlated data, the networked system adjusts a parameter in a walking profile of the user. The walking profile is then used to determine time estimates that are used to schedule services that require walking by a user.

Abstract: An image processing device, an image processing system, an image processing method, and a program capable of suppressing unnaturalness of color of an object extracted from a color image are provided. An image processing device includes an object area determination unit that determines an object area, a mask image generation unit that generates a mask image, an object image generation unit that generates an object image on the basis of the object area, a color determination unit that determines a color to be subtracted from colors to be applied to the object area and sets a smaller number of colors than those of the object area as colors of the object image, and a probability calculation unit that calculates a probability of pixels of the mask image being pixels of the object area, and the object image generation unit sets the colors set using the color determination unit as colors of an edge area of the object image on the basis of the probability.

Abstract: A voice service processing method and an apparatus are provided. The method includes: receiving, by a base station, voice configuration indication information from user equipment (UE), where the voice configuration indication information is used to indicate at least one voice configuration supported by the UE; and configuring, by the base station, a voice transmission scheme for the UE based on the voice configuration indication information. The UE can initiate a voice service on a 5G network, and a high-quality and convenient voice service can be provided for a user.

Abstract: An electronic device comprising: a memory; a communication unit for exchanging communications with a wearable device and an external device; and at least one processor that is operatively coupled to the memory, configured to: detect an event that is associated with a connection with the external device; identify a function that is associated with the external device in response to the event; and transmit to the wearable device an instruction for executing the function, wherein the instruction is transmitted via the communications unit.

Abstract: A self-position estimation apparatus includes an image capturing unit capturing driving images and reference images at a plurality of positions along a predetermined driving route, a detection unit detecting feature points on each of the driving images and feature points on each of the reference images, a storage unit storing map information which includes the feature points on each of the reference images and a position and a posture of the image capturing unit at a time each of the reference images is captured by the image capturing unit, and an estimation unit selecting a similar image similar to one of the driving images from the reference images to correlate the feature points on the one of the driving images and feature points on the similar image, the estimation unit estimating a position and a posture of an own vehicle a predetermined driving route based on a correlation result.

Abstract: Described is a smartphone lock box system that is used to track and record when and how long a mobile computing device is locked or secured in a container, such as a box, a sleeve or the like, without access by the owner of the mobile computing device. The smartphone lock box system is used to help the owner of a mobile computing device disconnect from the mobile computing device to devote time and attention to other tasks. The smartphone lock box system includes a container that holds at least one mobile computing devices such as a smartphone or tablet. The mobile computing device operating a lock box application senses it is within the container and records and reports the amount of time the mobile computing device is in the container and tracks the frequency that the user checks or removes the phone from the container.

Abstract: Systems and methods for semantic labeling of point clouds using images. Some implementations may include obtaining a point cloud that is based on lidar data reflecting one or more objects in a space; obtaining an image that includes a view of at least one of the one or more objects in the space; determining a projection of points from the point cloud onto the image; generating, using the projection, an augmented image that includes one or more channels of data from the point cloud and one or more channels of data from the image; inputting the augmented image to a two dimensional convolutional neural network to obtain a semantic labeled image wherein elements of the semantic labeled image include respective predictions; and mapping, by reversing the projection, predictions of the semantic labeled image to respective points of the point cloud to obtain a semantic labeled point cloud.

Abstract: An information handling system operating a predictive simultaneous localization and mapping (SLAM) system may comprise a camera mounted to a wearable headset capturing an image of a landmark, a positional sensor mounted to the wearable headset measuring a current positional state of the headset, and a network adapter receiving a stored SLAM frame, including an identification and position of the landmark within a previously captured image. A processor executing code instructions of the predictive SLAM system may generate a current SLAM frame based on the image captured via the camera, determine a Kalman gain associated with an observed location of the landmark based on the current SLAM frame and the stored SLAM frame, and determine a corrected position of the wearable headset based on a previously measured positional state of the headset, the current positional state of the headset, the current SLAM frame, and the Kalman gain.

Abstract: A system and method of analyzing a biological sample using an imaging system are disclosed. An image acquisition module instructs the imaging system to obtain a label free image of a training biological sample and in response receives a first training image. The image acquisition module also instructs the imaging system to cause the training biological sample to fluoresce and obtain an image of the training biological sample undergoing fluorescence, and in response receives a second training image. An analysis module analyzing the second training image to generate a plurality of training cell characteristics, wherein each of the plurality training cell characteristics is associated with one of a plurality of training cells that comprise the training biological sample.

Abstract: Certain aspects of the present disclosure provide techniques for providing an automated callback service to a user. An example technique includes receiving an indication of a product installation failure, which includes an error code, a context of the computing device, and a product identifier. Based on the product identifier, a phone number is retrieved that is associated with the user of the computing device. A set of solutions predicted to resolve the installation failure is retrieved, based on the error code and the context. A callback is established to the user, and the user is connected with a virtual agent that will provide solutions from the set of solutions in the ranking order retrieved until a solution is determined to resolve the product installation error. The ranking of the predicted solutions is updated for other users in the future who may face a similar product installation error.

Abstract: According to various embodiments of the disclosure, an electronic device and a method of executing a function of the electronic device comprise at least one communication circuit, a speaker, a microphone, at least one processor operatively connected with the communication circuit, the speaker, and the microphone, and a memory operatively connected with the at least one processor, wherein the memory stores instructions which, when executed by the at least one processor cause the electronic device to: perform a call with a first external electronic device through the communication circuit, activate a voice-based intelligent service while the call is performed, identify a voice input through the microphone while the call is performed, and transmit data associated with the voice input to an external server through the communication circuit at least in part for automatic speech recognition (ASR) and/or natural language understanding (NLU).

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of an object by an imaging device, the hyperspectral image of the object comprising a three-dimensional set of images of the object, each image in the set of images representing the object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the object, select a region of interest in the hyperspectral image, the region of interest comprising at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of a food object by an imaging device, the hyperspectral image of the food object comprising a three-dimensional set of images of the food object, each image in the set of images representing the food object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the food object, select a region of interest in the hyperspectral image, the region of interest comprising a subset of at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the food object and determine that the hyperspectral image indicates a foreign object.

Abstract: A user equipment (UE) can receive, from an eNodeB, a serving PLMN system information block (SIB)19 for a carrier frequency of a serving PLMN of the UE. The UE can acquire inter-frequency and inter-PLMN discovery system information acquisition assistance signaling information from the SIB19. The UE can process a non-serving PLMN SIB19 for one or more carrier frequencies of a non-serving PLMN using the inter-frequency and inter-PLMN discovery system information acquisition assistance signaling information. The UE can identify inter-frequency and inter-PLMN discovery announcement rate information and monitoring control configuration information for the one or more carrier frequencies of the non-serving PLMN to enable the UE to perform device-to-device (D2D) discovery with a UE in the non-serving PLMN according to the inter-frequency and inter-PLMN discovery announcement rate information and monitoring control configuration information.

Abstract: Provided are a method of reselecting a cell by a terminal in a wireless communication system and a device supporting the same. A terminal may measure a cell on the basis of a priority, may calculate a ranking of the cell, using a cell measurement result, and may reselect a cell having the highest ranking. Otherwise, the terminal may measure a cell and evaluate a cell reselection criterion on the basis of a priority, may calculate a CE level with respect to a cell satisfying the cell reselection criterion evaluation, using a cell measurement result, and may reselect a cell having the lowest CE level. The terminal may be a terminal operating in a coverage extension mode and the coverage extension mode enables the cell measurement to be performed for a longer time than a normal mode.

Abstract: A telecom connectivity service provider (TCSP) and a method for allocating an infrastructure resource to a virtual network operator (VNO). A TCSP control element sends to a downstream control element, a request for a portion of the infrastructure to be allocated to the TCSP by an infrastructure provider (InP) and receives a response from the downstream control element providing access to and control of the allocated infrastructure. The TCSP control element can pool the allocated infrastructure with other resources allocated to the TCSP and/or communicate with an upstream control element for providing access to and control of the allocated infrastructure to the VNO. The downstream control element is a local InP control element or a downstream TCSP control element. The upstream control element is a VNO control element or an upstream TCSP control element.

Abstract: A workflow for rock sample image processing is established to determine geometrical parameters of rock texture. Individual pores and grains are identified using Hoshen-Kopelman multi-cluster labeling algorithm and watershedding technique. Separated elements are fitted with ellipses and pore/grain size distributions, aspect ratios and orientations of fitting ellipses are obtained. Such information is especially valuable in interpretation and forward modeling of dielectric responses using textural models. Rock sample images by high-resolution confocal microscopy are selected to test the workflow and results are analyzed.

Abstract: Systems and methods for wireless discovery and connectivity in 802.11 networks. A management frame from an access point (AP) or personal basic service set (PBSS) control point (PCP) indicates which designated channels are operating and which are non-operating, for purposes of subsequent wireless communications, such as Association Beamforming Training (A-BFT). The management frame contains a bitmap or other forms for indicating which of the designated channels are operating and which are non-operating. In response to the information received through the management frame, one or more stations (STA) can select any one of the operating channels for transmitting of frames in A-BFT communication or other access periods in the Beacon Interval.

Abstract: Methods and systems for artificial intelligence based medical image segmentation are disclosed. In a method for autonomous artificial intelligence based medical image segmentation, a medical image of a patient is received. A current segmentation context is automatically determined based on the medical image and at least one segmentation algorithm is automatically selected from a plurality of segmentation algorithms based on the current segmentation context. A target anatomical structure is segmented in the medical image using the selected at least one segmentation algorithm.