Abstract: The present disclosure provides a cross-correlation based method, a system and a storage medium for blind electromagnetic interference Doppler estimation from a single satellite geolocation system. The method includes at a first time, calculating a power spectral density (PSD) of a received signal; smoothing the PSD of the received signal using moving window average, and saving the smoothed PSD of the received signal as PSD0; at a next time, calculating a PSD of another received signal; smoothing the PSD of the another received signal using moving window average, and saving the smoothed PSD of the another received signal as PSD1; performing cross correlation between PSD0 and PSD1 to obtain a cross-correlation result; determining a peak position from the cross-correlation result; and obtaining a Doppler estimation based on a peak position shift between the peak position and a reference position.

Abstract: A method may include obtaining an image of an object; obtaining a target artifact identification model; determining target artifact feature information by inputting the image into the target artifact identification model, the target artifact feature information indicating a feature of one or more artifacts in the image; obtaining a target artifact extent determination model; determining target artifact extent indication information by inputting the image and the target artifact feature information into the target artifact extent determination model, the target artifact extent indication information indicating an influence extent of the one or more artifacts on an image quality of the image; in response to determining that the influence extent is greater than or equal to the extent threshold, outputting a notice of the one or more artifacts of the image.

Abstract: A method for modulating data for transmission within a communication system. The method includes establishing a time-frequency shifting matrix of dimension N×N, wherein N is greater than one. The method further includes combining the time-frequency shifting matrix with a data frame to provide an intermediate data frame. A transformed data matrix is provided by permuting elements of the intermediate data frame. A modulated signal is generated in accordance with elements of the transformed data matrix.

Abstract: Provided is an information processing apparatus which includes a line-of-sight estimator, a correction amount calculator, and a registration determination section. The line-of-sight estimator calculates an estimation vector obtained by estimating a direction of a line of sight of a user. The correction amount calculator calculates a correction amount related to the estimation vector on the basis of at least one object that is within a specified angular range that is set using the estimation vector as a reference. The registration determination section determines whether to register, in a data store, calibration data in which the estimation vector and the correction amount are associated with each other, on the basis of a parameter related to the at least one object within the specified angular range.

Abstract: Disclosed are a diagnostic information processing method and apparatus based on a medical image, and a storage medium, to achieve disease grading based on a medical image. The method includes: acquiring a first lung medical image of a subject; acquiring image parameters of an affected area in the first lung medical image; and determining, according to the image parameters of the affected area, a disease grade of lungs of the subject corresponding to information of the first lung medical image. Using the solution provided by the present invention, the image parameters of the affected area in the first lung medical image can be acquired, and then the disease grade of the lungs of the subject corresponding to the information of the first lung medical image can be determined according to the image parameters of the affected area, so that a disease can be graded based on a medical image.

Abstract: A blood vessel specifying device (1) includes an image processing device (31) configured to subject an image for analysis of a target part (2) to image processing to acquire blood vessel information including positions and shapes of blood vessels included in the target part (2), an evaluation device (32) configured to use the blood vessel information to assign a point rating regarding a parameter that indicates a conformity to a particular purpose with respect to the blood vessels included in the image for analysis depending on a degree of the conformity, and a specification device (33) configured to specify conforming blood vessels conforming to the purpose from the blood vessels included in the target part (2) in accordance with rating points of the parameter.

Abstract: Embodiments described herein provide a masked self-training (MaST) which is an unsupervised learning approach leveraging two complimentary sources of supervision: pseudo-labels and raw image pixels. Specifically, MaST jointly optimizes three objectives to finetune a pre-trained classification model on unlabeled images: (1) self-training objective to learn global task-specific class prediction; (2) masked image modeling objective to learn local pixel-level information; (3) global-local feature alignment objective to bridge the knowledge learned from the two sources of supervision.

Abstract: An image encoding/decoding method and apparatus are provided. An image decoding method according to the present disclosure includes: receiving an image, in which a first atlas for a basic view of a current image and a second atlas for an additional view of the current image are merged; extracting an image divided in a predetermined image unit within the first atlas and the second atlas; dividing the first atlas and the second atlas in the predetermined image unit; and reconstructing the image divided in the predetermined image unit, wherein the dividing of the first atlas and the second atlas in the predetermined image unit may non-uniformly divide the first atlas and the second atlas.

Abstract: Methods and systems for automated video segmentation are disclosed. A sequence of video frames having video segments of contextually-related sub-sequences may be received. Each frame may be labeled according to segment and segment class. A video graph may be constructed in which each node corresponds to a different frame, and each edge connects a different pair of nodes, and is associated with a time between video frames and a similarity metric of the connected frames. An artificial neural network (ANN) may be trained to predict both labels for the nodes and clusters of the nodes corresponding to predicted membership among the segments, using the video graph as input to the ANN, and ground-truth clusters of ground-truth labeled nodes. The ANN may be further trained to predict segment classes of the predicted clusters, using the segment classes as ground truths. The trained ANN may be configured for application runtime video sequences.

Abstract: The disclosed technology is generally directed to identifying media documents embedded within other media documents. In one example of the technology, source fingerprints are generated from input images using a source machine-learning model. The input images are derived from the media documents. Target fingerprints are generated from the input images using a target machine-learning model. The source machine-learning model includes a first neural network. The target machine-learning model includes a second neural network that is different from the first neural network. The source machine-learning model was trained in parallel with the target machine-learning model. Candidate media-document pairs from the media documents are determined based on the source fingerprints and the target fingerprints. Each candidate media-document pair includes a media document that is a candidate for being embedded in another media document.

Abstract: A computer-implemented method is for providing at least one first metadata attribute associated with a medical image. The method includes receiving the medical image and the at least one first metadata attribute. Therein the at least one first metadata attribute includes an attribute tag and a provisional attribute value. Furthermore, the method includes applying a first trained function to the medical image to determine an image-based attribute value. Furthermore, the method includes determining a final attribute value based on the provisional attribute value and the image-based attribute value. Furthermore, the method includes providing the at least one first metadata attribute. Therein the at least one first metadata attribute includes the attribute tag and the final attribute value.

Abstract: The present application relates to methods, systems, and devices related to digital wireless communication, and more specifically, to techniques related to providing UAC parameters to a UE capable of performing a barring check based on the received parameters. A method for wireless communication can include receiving, by a wireless node, a first message that includes a set of access control parameters from a network node. The method can also include performing, by the wireless node, a barring check to determine whether a certain access attempt is allowed using the set of access control parameters.

Abstract: The present invention relates to the generation of artificial MRI images of the liver. The invention also relates to a method, a system and a computer program product for generating MRI images of the liver.

Abstract: Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include, at least, detecting an optical sight to align with an associated agricultural object, tracking the agricultural objects relative to the optical sight, predicting a parameter to track in association with agricultural object, and activating an emitter to apply an action based on the parameter.

Abstract: An image processing apparatus includes: a first obtainment unit configured to obtain a plurality of captured images of an object captured under a plurality of image capture conditions; a second obtainment unit configured to obtain information on a material of the object; and an estimation unit configured to estimate a distribution of normals of the object based on the plurality of captured images and the information on the material.

Abstract: Systems and techniques are provided for vision perception processing. An example method can include determining an attention demand score or characteristic per region of a frame from a sequence of frames; generating attention votes per region of the frame based on the attention demand score or characteristic per region, the attention votes per region providing attention demands and/or attention requests; determining an attention score or characteristic per region of the frame based on a number of attention votes from one or more computer vision functions; based on the attention score or characteristic per region of the frame, selecting one or more regions of the frame for processing using a neural network; and detecting or tracking one or more objects in the one or more regions of the frame based on processing of the one or more regions using the neural network.

Abstract: Disclosed is a method and apparatus for storing geofencing information within a SIM card. The geofencing information within the SIM (subscriber identity module) card is updated using an OTA (over the air) Update Server. Such geofencing information for a particular enterprise network is pushed to the SIM within a UE (user equipment) upon detecting that the UE is near, or within, the campus of an enterprise network. In some embodiments, the UE requests an update from the OTA Update Server.

Abstract: Methods and apparatuses for performing automated detection of lung slide using a computing device (e.g., an ultrasound system, etc.) are disclosed. In some embodiments, the techniques determine lung sliding using one or more neural networks. In some embodiments, the neural networks are part of a process that determines probabilities of the lung sliding at one or more M-lines. In some embodiments, the techniques display one or more probabilities of lung sliding in a B-mode ultrasound image.

Abstract: For an orthodontic appliance that may be easily and accurately attached to teeth and a method of manufacturing the orthodontic appliance, an orthodontic appliance including a slot configured to accommodate an orthodontic wire to be inserted and a contact portion configured to contact a positioner located on a surface of a tooth and a method of manufacturing the orthodontic appliance are provided.

Abstract: Disclosed is a method for analyzing a lesion based on a medical image, which is performed by a computing device. The method may include: obtaining positional information of a suspicious nodule which exists in the medical image; generating a mask for the suspicious nodule based on a patch of the medical image corresponding to the positional information; and determining a class for a state of the suspicious nodule based on the patch of the medical image and the mask for the suspicious nodule.