Abstract: Disclosed are an apparatus and a method for selecting a beam in an electronic device. An electronic device includes: a plurality of antennas configured to form beams in different directions; and at least one processor, wherein the at least one processor is configured to: control the plurality of antennas to form a wide beam, determine a transmission beam pattern of a transmitting side through the wide beam, control the plurality of antennas to form a reception beam, and determine a reception beam pattern to be used for receiving a signal from the transmitting side.

Abstract: A change in a state of a user is more properly recognized by the user. A notification device includes a physical condition information acquiring section or a makeup information acquiring section, a light emitting section and a display section serving as a notifying section, a control section, and a determining section. The physical condition information acquiring section or the makeup information acquiring section acquires face information. The light emitting section and the display section serving as the notifying section perform a notification on the basis of the face information. The determining section determines a change between the face information before the notification and the face information after the notification. The control section controls the notification by the light emitting section and the display section serving as the notifying section on the basis of a determination result by the determining section.

Abstract: Methods and apparatus are disclosed to determine a consumer classification segment. A disclosed example method involves generating, with a processor, a list of consumer classification segments based on geographic indicators associated with a mobile device, associating, with the processor, the mobile device with a first consumer classification segment of the list of consumer classification segments if the geographic indicators were retrieved while a first application was executed, and associating, with the processor, the mobile device with a second consumer classification segment of the list of consumer classification segments if the geographic indicators were retrieved while a second application was executed.

Abstract: A method, system and computer program product for region proposals are disclosed. The method includes generating a map of a video frame by calculating a plurality of pixel-level values. Each pixel-level value corresponds to a respective one of a plurality of pixels and provides an associated indication of how likely the respective one of the plurality of pixels forms part of a particular object of interest.

Abstract: Systems and methods for virtual agronomic sensing are provided. In embodiments methods comprise receiving first agronomic data for a first geographic location comprising sensor data from agronomic sensors at the first geographic location; receiving first agronomic information for the first geographic location; and generating first predictive agronomic data for the first geographic location using the first agronomic data for the first geographic location and the first agronomic information for the first geographic location.

Abstract: A vegetation index calculation apparatus (10) is provided with a learning model generation unit (11) that generates a learning model, by using an image of a crop targeted for calculation of a vegetation index and an image of plants other than the crop to learn a feature amount of the image of the crop, an image acquisition unit (12) that acquires an aerial image of a target region where the crop is being grown, a specification unit (13) that applies the aerial image acquired by the image acquisition unit (12) to the learning model generated by the learning model generation unit (11), and specifies the image of the crop in the aerial image acquired by the image acquisition unit (12), and a vegetation index calculation unit (14) that calculates the vegetation index of the crop, using the image of the crop specified by the specification unit (13).

Abstract: A method for learning deep convolutional features specifically designed for correlation filter based visual tracking includes the steps of, selecting a first image from a first image patch; selecting a second image from a second image patch; forward propagating selected first image by a convolutional neural network model formula, the formula has random weights with zero mean for the parameters; forward propagating selected second image by the convolutional neural network model formula; computing correlation filter using forward propagated second image and centered correlation response; circularly correlating forward propagated first image and computed correlation filter to generate predicted response map; calculating the loss by comparing the predicted response map with desired correlation corresponding selected first image and second image and updating the parameters of the convolutional neural network model formula according to calculated loss.

Abstract: Apparatuses, systems, and techniques are described to determine locations of objects using images including digital representations of those objects. In at least one embodiment, a gaze of one or more occupants of a vehicle is determined independently of a location of one or more sensors used to detect those occupants.

Abstract: A multi-label generating system is configured to: store a first plurality of medical scans with corresponding global labels and a second plurality of medical scans with corresponding region labels, wherein the global labels each correspond to one of a set of abnormality classes and wherein each of the region labels correspond to one of the set of abnormality classes; generate a computer vision model by training on the first plurality of medical scans with the corresponding global labels and the second plurality of medical scans with the corresponding region labels; receive a new medical scan; generate global probability data based on the computer vision model, wherein the global probability data indicates a set of global probability values corresponding to the set of abnormality classes, and wherein each of the set of global probability values indicates a probability that a corresponding one of the set of abnormality classes is present in the new medical scan; and transmit the global probability data to a cli

Abstract: Systems and methods for localization for mobile devices are described. Some implementations may include accessing motion data captured using one or more motion sensors; determining, based on the motion data, a coarse localization, wherein the coarse localization includes a first estimate of position; obtaining one or more feature point maps, wherein the feature point maps are associated with a position of the coarse localization; accessing images captured using one or more image sensors; determining, based on the images, a fine localization pose by localizing into a feature point map of the one or more feature point maps, wherein the fine localization pose includes a second estimate of position and an estimate of orientation; generating, based on the fine localization pose, a virtual object image including a view of a virtual object; and displaying the virtual object image.

Abstract: For example, an apparatus may include one or more processors comprising circuitry to cause a first wireless device to generate a wakeup packet comprising a payload comprising at least one payload field modulated according to an On-Off keying (OOK) modulation, the payload field comprising a sequence of a plurality of codes to encode binary bit values of the payload field according to an encoding scheme having a code rate less than one, a first code of the encoding scheme representing a binary bit value of “0” comprising a first sequence of two or more bits comprising at least one bit having a value of “1”, and a second code of the encoding scheme representing a binary bit value of “1” comprising a second sequence of two or more hits comprising at least one bit having a value of “1”; and to transmit the wakeup packet to a second wireless device.

Abstract: A system for digital self-interference cancellation includes a filter that generates a reduced-noise digital residue signal; a channel estimator that generates a current self-interference channel estimate from a digital transmit signal, the reduced-noise digital residue signal, and past self-interference channel estimates; a controller that dynamically sets the digital transform configuration in response to changes in a controller-sampled digital residue signal; a predictor that modifies output of the channel estimator to compensate for a first time delay incurred in tuning the system for digital self-interference cancellation; and a channel memory that stores the past self-interference channel estimates.

Abstract: Embodiments herein disclose a method for handling dual registration of user equipment (UE) in a wireless communication system. The method includes registering the UE on a fourth generation Radio Access Technology (4G RAT) and a fifth generation RAT (5G RAT). Further, the method includes determining, by the UE, an occurrence of at least one event. Further, the method includes suspending, by the UE, the registration on the 5G RAT. Further, the method includes performing, by the UE, communication using the registration on the 4G RAT.

Abstract: A method and a device for improved training of a classifier. For this purpose, the device for detecting an object has a first image recording device, which is situated in a first position for recording the object from a first perspective. The device furthermore has a stored first classifier, which is configured to detect the object based on the recorded first perspective. At least one second image recording device is situated in a second position for recording the object from a second perspective, which differs from the first perspective. Furthermore, a data processing device is configured to detect the object recorded by the first image recording device based on the first classifier and to assign to the second perspective a class predetermined by the first classifier. This makes it possible to expand the existing classifier to include the detection of the object from different additional perspectives.

Abstract: For a wireless communications system, scalable orthogonal frequency division multiplexing (OFDM) numerology is incorporated in a manner that can apply to radio link transmissions in future wireless network for frequency division duplex (FDD) and time division duplex (TDD) communications.

Abstract: Disclosed is an image analysis method including inputting analysis data, including information regarding an analysis target cell to a deep learning algorithm having a neural network structure, and analyzing an image by calculating, by use of the deep learning algorithm, a probability that the analysis target cell belongs to each of morphology classifications of a plurality of cells belonging to a predetermined cell group.

Abstract: A system and method of selecting a frame capturing a short duration action from a video. The method including receiving a sequence of frames of the video; and determining a reference frame in the sequence of frames by detecting a predetermined action captured in one of a first plurality of frames from the sequence of video frames, the first plurality of frames being sampled from the sequence of frames at a first sampling rate lower than that of the sequence of frames. The method further comprises selecting a second plurality of frames from the sequence of frames, the second plurality of frames having a location associated with the reference frame in the sequence and being selected at a second sampling rate, the second sampling rate being higher than the first sampling rate; and selecting the frame capturing the short duration action from the second plurality of frames.

Abstract: In an approach for chemical detection for a water source, a processor receives, from a network device of a plurality of network devices, data, wherein the data includes at least one of image data, video data, chemical sensor data, and biosensor data. A processor updates a predictive model with the data. A processor receives a table of possible chemical compositions from the predictive model. A processor determines to send an alert based on the table of possible chemical compositions. A processor sends the alert to a user device.

Abstract: Systems and methods for utilizing dynamic codes in a dynamic system comprising neural networks are disclosed. In an exemplary embodiment, training data is transmitted to an encoder block, the encoder block having an encoder neural network. Training data is encoded utilizing the encoder neural network of the encoder block, and then decoded by a decoder block, the decoder block having a decoder neural network. An end-end error is determined by comparing the training data that was transmitted to the encoder block against the decoded training data that was received from the decoder block. Encoder/decoder parameters to minimize the end-end error are optimized and transmitted. Upon receipt of the encoder/decoder parameter updates, the encoder block and the decoder block are initialized.

Abstract: To enable a more accurate estimation of the center of a pupil even in a situation in which it is difficult to capture an image of the entire pupil. An information processing device includes: an acquisition unit that acquires information regarding an iris in an eyeball; and an estimation unit that estimates a center position of a pupil in the eyeball on the basis of the information regarding the iris.