Abstract: Methods and systems for providing a dataset of human in-bed poses include simultaneously gathered images of in-bed poses of humans from imaging modalities including red-green-blue (RGB) and one or more of long wavelength infrared (LWIR), depth imaging, and pressure mapping. The images are obtained under a lighting condition and a cover condition. The dataset can be used to train a model of estimating human in-bed poses and for methods of estimating human in-bed poses. Methods and systems of estimating three-dimensional human poses from two-dimensional input images are provided.

Abstract: A computer-implemented method of reducing noise in magnetic resonance (MR) images is provided. The method includes executing a neural network model of analyzing MR images, wherein the neural network model is trained with a pair of pristine images and corrupted images. The pristine images are the corrupted images with noise reduced, and target output images of the neural network model are the pristine images. The method also includes receiving first MR signals and second MR signals, reconstructing first and second MR images based on the first MR signals and the second MR signals, and analyzing the first MR image and the second MR image using the neural network model. The method further includes deriving a denoised MR image based on the analysis, wherein the denoised MR image is a combined image based on the first MR image and the second MR image and outputting the denoised MR image.

Abstract: The present disclosure provides methods and apparatuses for image processing and image classification. In one embodiment, the method for image processing comprises: receiving an image; obtaining a first classification result for the image based on a classification model; processing the image for classification based on a preset process, and providing a processing result into a re-ranking model to obtain a second classification result for the image; and determining a target classification result for the image, based on the first classification result and the second classification result.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for generating and/or adapting automated assistant content according to a distance of a user relative to an automated assistant interface that renders the automated assistant content. For instance, the automated assistant can provide data for a client device to render. The client device can request additional data when the user relocates closer to, or further from, the client device. In some implementations, a request for additional data can identify a distance between the user and the client device. In this way, the additional data can be generated or selected according to the distance in the request. Other implementations can allow an automated assistant to determine an active user from a group of users in an environment, and determine a distance between the active user and the client device in order that any rendered content can be tailored for the active user.

Abstract: A method for visualization of digitized slides is disclosed. The method comprises retrieving, by one or more computer processors, a digitized slide, determining, by the one or more computer processors, one or more visualization components of the digitized slide, generating, by the one or more computer processors, a virtual slide corresponding to the digitized slide based on the one or more visualization components, and displaying, by the one or more computer processors, a visualization of the virtual slide.

Abstract: A spinal surgery training process includes the steps of capturing a plurality of 2D images for each of a plurality of spines, generating a curve of each spine from the respective 2D images based on locations of select vertebrae in each of the spines, grouping the spines into one of a number of groups based on similarity to produce groups of spines having similarities, performing the capturing, generating, determining and grouping steps at least once prior to surgery and at least once after surgery to produce pre-operative groups and their resultant post-operative groups, and assigning surgical methods and a probability to each of the post-operative groups indicating the probability that a spinal shape of the post-operative group can be achieved using the surgical methods. An outcome prediction process for determining surgical methods can be implemented once the training process is complete.

Abstract: An information processing program causes a computer to execute a process including: generating, by inputting a captured image into a machine learning model, skeleton information on a person included in the captured image; detecting, by using the skeleton information, a specific motion of the person related to an object included in the captured image; specifying, by using positional information on the person included in the captured image, a first area in which the person is located at a time of detection of the specific motion from among a plurality of areas; specifying, by reading setting information recorded in a memory, first setting information that is associated with the first area; and identifying, based on the first setting information, a priority level of a notification of an alert related to the specific motion of the person related to the object.

Abstract: An apparatus and method for training and using a computing operation for digital image processing are provided. The apparatus and method may be used for 3-dimensional medical images. An exemplary method for digital image processing comprises: receiving an image displaying at least one detectable structure, determining the detectable structure; segmenting the image to obtain a segmentation mask that is associated with a geometric shape and comprises at least one quantifiable visual feature; generating a mesh based on the quantifiable visual feature; computing at least on quantifiable visual parameter based on the mesh; extracting quantifiable visual data from the image based on the quantifiable visual parameter; training the computing operation with the quantifiable visual data.

Abstract: A method for generating virtual microwave (MW) phantoms at a specific MW frequency or multiple MW frequencies, comprising generating virtual MW phantoms using a generative neural network (generator) and identifying the authenticity of the virtual MW phantoms using a discriminative neural network (discriminator).

Abstract: A detection and communication module arranged to implement a face detection function and an optical wireless communication function, and including a processing unit, a transmission chain and a reception chain, the processing unit being arranged to transmit via the transmission chain a detection signal, to receive via the reception chain the detection signal following its reflection on a face surface of an individual, and to evaluate a distance between the detection and communication module and the face surface of the individual, the processing unit being further arranged to transmit via the transmission chain a transmitted optical wireless communication signal containing data to be transmitted, and to receive via the reception chain a received optical wireless communication signal.

Abstract: Disclosed herein is a system and method for improving the accuracy of an object detector when trained with a dataset having a significant number of missing annotations. The method uses a novel Background Recalibration Loss (BRL) which adjusts the gradient direction according to its own activation to reduce the adverse effect of error signals by replacing the negative branch of the focal loss with a mirror of the positive branch when the activation is below a confusion threshold.

Abstract: Aspects of this disclosure relate to a multiplexer with an acoustic assisted trap circuit. The multiplexer includes a first acoustic wave filter and a second acoustic wave filter. The first acoustic wave filter can include a bulk acoustic wave resonator. The second acoustic wave filter can include a surface acoustic wave resonator and an impedance network. The surface acoustic wave resonator and the impedance network can together provide a trap for a harmonic associated with the first acoustic wave filter.

Abstract: A method includes determining, based on an image having an initial viewpoint, a depth image, and determining a foreground visibility map including visibility values that are inversely proportional to a depth gradient of the depth image. The method also includes determining, based on the depth image, a background disocclusion mask indicating a likelihood that pixel of the image will be disoccluded by a viewpoint adjustment. The method additionally includes generating, based on the image, the depth image, and the background disocclusion mask, an inpainted image and an inpainted depth image. The method further includes generating, based on the depth image and the inpainted depth image, respectively, a first three-dimensional (3D) representation of the image and a second 3D representation of the inpainted image, and generating a modified image having an adjusted viewpoint by combining the first and second 3D representation based on the foreground visibility map.

Abstract: Herein disclosed are robotic dentistry methods comprising tooth extraction and crown preparation. Robotic tooth extraction may comprise determining if the correct tooth is targeted, based on a scanned image; determining a decay state of the tooth based on the scanned image; selecting an extraction technique determined as a function of the decay state; and extracting the tooth using the selected extraction technique. Robotic crown preparation may comprise receiving an initial reduction plan to reduce a tooth; presenting, to a dentist for approval, the initial reduction plan for approval; upon approval, reducing the tooth according to the approved initial reduction plan; upon rejection, modifying the initial reduction plan based on dentist input; receiving the modified reduction plan to reduce the tooth; presenting, to a dentist for approval, the modified reduction plan for approval; and upon approval of the modified reduction plan, reducing the tooth according to the approved modified reduction plan.

Abstract: The present disclosure belongs to the field of defect detections and discloses a method for constructing a defect detection model, a method for detecting a defect and a related apparatus, obtaining an initial training image, and adding a simulated anomaly to the initial training image to obtain a simulated anomaly training image; training a preset defect recognition model according to the initial training image and the simulated anomaly training image to obtain defect position information and mask prompt information; training a preset defect segmentation model according to the defect position information and the mask prompt information; and fusing the trained defect recognition model and defect segmentation model to obtain a defect detection model; the defect recognition model includes a teacher network branch, a student network branch and an autoencoder network branch; and an output difference between the teacher network branch and the student network branch is the defect position information.

Abstract: In one embodiment, a method includes receiving an image generated by a camera associated with a vehicle. The image includes a point of interest (POI) associated with a physical object. The method also includes determining a number of pixels from the POI of the image to an edge of the image. The edge of the image represents a location of the camera. The method further includes determining an offset distance from the POI to a Global Positioning System (GPS) unit associated with the vehicle using the number of pixels.

Abstract: A robot system includes a robot installed in a work area and controlled by a second control device, a 3D camera operated by an operator, a sensor that is disposed in a manipulation area that is a space different from the work area, and wirelessly detects position information and posture information on the 3D camera, a display, and a first control device. The first control device acquires image information on a workpiece imaged by the 3D camera, acquires, from the sensor, the position information and the posture information when the workpiece is imaged by the 3D camera, displays the acquired image information on the display, forms a three-dimensional model of the workpiece based on the image information, and the acquired position information and posture information, displays the formed three-dimensional model on the display, and outputs first data that is data of the formed three-dimensional model to the second control device.

Abstract: A method for classifying a human-object interaction includes identifying a human-object interaction in the input. Context features of the input are identified. Each identified context feature is compared with the identified human-object interaction. An importance of the identified context feature is determined for the identified human-object interaction. The context feature is fused with the identified human-object interaction when the importance is greater than a threshold.

Abstract: Disclosed is a system and a method for geo-referencing an object on a floor. The method comprises receiving a camera frame providing view of a section of the floor, receiving a detailed floor plan of the floor, selecting a first area from the section of the floor in which the object needs to be tracked and defining a plurality of reference points. Herein, at least one of the pluralities of reference points is close to a mid-point along one of corresponding axes of the first area. The method further comprises mapping the plurality of reference points to the floor plan, processing the camera frame to determine if the object has been placed in the first area and geo-referencing the one or more object in the floor plan if the object is determined to be placed in the first area.

Abstract: Provided are a communication link adjustment method and apparatus, an electronic device, and a readable medium. The method includes that: interference information of a communication link under a multi-connection scenario is acquired; whether an isolation degree value of the communication link exceeds a range defined by a preset isolation degree threshold is determined according to the interference information; and in a case where the isolation degree value of the communication link exceeds the range defined by the preset isolation degree threshold, the communication link is adaptively adjusted according to the isolation degree value and an isolation degree adjustment mapping table until the isolation degree value meets a requirement for a wireless performance index, wherein the isolation degree adjustment mapping table includes a mapping relationship between isolation degree values and path parameters.