Abstract: A method to generate predictive models to automatically classify, medical or veterinary images derived from original images is disclosed. The method is computer-implemented and includes the steps: selection of at least one class of interest wherein the classes of interest characterize predictions; construction of a database containing a plurality of data structures representative of derived images and generated by processing original images in such a way that they can be used for surrogate of real biopsies with real staining media performed by means of medical imaging systems; association to the classes of interest of said data structures; and training of at least one model using the data structures on the basis of the differences in the distribution of expression levels of measured characteristics of the derived images, to classify each of the derived images in classes of interest.

Abstract: Provided is a channel identification method. The method includes: acquiring channel data of a terminal; constructing a first feature vector based on the channel data, where the first feature vector represents a numerical value set of cross-correlation values, which change along with time intervals, between channel data at different moments and the channel data themselves and between the channel data at different moments and subsequent channel data at different time intervals; and inputting the first feature vector into a predetermined prediction model to predict a speed of the terminal, or to predict a speed type of a cluster to which the terminal belongs. Further provided are an adaptive transmission method and apparatus based on the channel identification method, a transmission device, a base station, and a computer storage medium.

Abstract: Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for identifying data processing activities associated with various data assets based on data discovery results. In accordance various aspects, a method is provided comprising: identifying and scanning data assets to detect a subset of the data assets, wherein each asset of the subset is associated with a particular data element used for target data; generating a prediction for each pair of data assets of the subset on the target data flowing between the pair; identifying a data flow for the target data based on the prediction generated for each pair; and identifying a data processing activity associated with handling the target data based on a correlation identified for the particular data element, the subset, and/or the data flow with a known data element, subset, and/or data flow for the data processing activity.

Abstract: A method of classifying pressure inputs in a sensing array, in which the sensing array comprises a plurality of sensing elements responsive to pressure inputs is described. The method comprises steps of identifying a plurality of pressure inputs in the sensing array and converting the plurality of pressure inputs into an output image. The output image is compared with a data set comprising a plurality of images of undesirable pressure inputs by means of an artificial neural network. A mask is applied which is consistent with the output image to remove undesirable pressure inputs.

Abstract: The present disclosure provides a medical image segmentation method. The medical image segmentation method includes acquiring a to-be-processed medical image set, the to-be-processed medical image set including a plurality of to-be-processed medical images corresponding to different time points, processing the to-be-processed medical image set in a time dimension according to the to-be-processed medical images and the time points corresponding to the to-be-processed medical images to obtain a temporal dynamic image, and extracting a target region feature from the temporal dynamic image by using a medical image segmentation model, to acquire a target region.

Abstract: An intubation assistance device includes an electronic controller configured to: generate a patient respiratory tract geometry model of at least a portion of a human respiratory tract by inputting one or more patient variables into a statistical shape model (SSM) of at least a portion of the human respiratory tract; select a recommended endotracheal tube (ETT) size by modeling at least one ETT model inserted into the patient respiratory tract geometry model to form a virtual fit model and estimating at least one fit parameter based on the virtual fit model; and display the recommended ETT size on a display device.

Abstract: Aspects of this disclosure relate to a multiplexer with an acoustic assisted trap circuit. The multiplexer includes an acoustic wave filter with an acoustic wave resonator and an impedance network that together provide a trap for a harmonic associated with another acoustic wave filter of the multiplexer. The acoustic wave filter can have an edge of a passband that is farther from the harmonic than other acoustic filters of the multiplexer.

Abstract: A passive human detection method and apparatus, a device, and a medium are provided. The passive human detection method includes: acquiring an infrared radiation signal in an environment, and acquiring a temperature of a target object; emitting an electromagnetic wave into the environment, and acquiring a reflected echo signal; determining a position of the target object in the environment based on the echo signal; matching a threshold range based on the position of the target object; and comparing the temperature of the target object with the threshold range to determine detection information of a human in the environment. The passive human detection method combines electromagnetic wave detection and thermal imaging to detect whether there is a human in the current environment. The passive human detection method can effectively filter out interference signals, greatly improving the accuracy and sensitivity of human detection.

Abstract: A system and method for image-based monitoring of an object inserted into a patient is disclosed. A model can be trained for an object configured to be inserted into a patient as part of a medical procedure, the trained model being generated from one or more machine learning algorithms that are trained on annotated images of the object with spatial information of the object. An imaging computer system can receive one or more images of the object inserted within the patient captured by an imaging device positioned external to the patient. The imaging computer system can further determine, based on applying the trained model to the one or more images of the object, current spatial information of the object within the patient. A display can output the one or more images and the current spatial information of the object.

Abstract: Techniques are provided for generating a digital image of simulated handwriting using an encoder-decoder neural network trained on images of natural handwriting samples. The simulated handwriting image can be generated based on a style of a handwriting sample and a variable length coded text input. The style represents visually distinctive characteristics of the handwriting sample, such as the shape, size, slope, and spacing of the letters, characters, or other markings in the handwriting sample. The resulting simulated handwriting image can include the text input rendered in the style of the handwriting sample. The distinctive visual appearance of the letters or words in the simulated handwriting image mimics the visual appearance of the letters or words in the handwriting sample image, whether the letters or words in the simulated handwriting image are the same as in the handwriting sample image or different from those in the handwriting sample image.

Abstract: The present disclosure is related to systems and methods for processing X-ray images. A method for processing an X-ray image may include obtaining an X-ray image; and determining a metal image based on the X-ray image by using a trained metal detection model. The metal image includes information of a metal object in the X-ray image.

Abstract: Multimodal techniques are described for classifying start pages and/or document types of an unstructured document image package. To that end, some implementations of the disclosure relate to a method, including: obtaining a document image file including multiple pages and multiple document types; generating, for each page of the multiple pages, using multiple independent trained models, multiple independent predictions, each of the multiple independent predictions indicating: whether or not the page is a first page of a document, or a document type of the multiple document types that the page corresponds to; and generating, for each page of the multiple pages, based on the multiple independent predictions, using a neural network, a final prediction output indicating whether or not the page is the first page of a document, or one of the multiple document types that the page corresponds to.

Abstract: Methods and systems are described for providing end-to-end beamforming. For example, end-to-end beamforming systems include end-to-end relays and ground networks to provide communications to user terminals located in user beam coverage areas. The ground segment can include geographically distributed access nodes and a central processing system. Return uplink signals, transmitted from the user terminals, have multipath induced by a plurality of receive/transmit signal paths in the end to end relay and are relayed to the ground network. The ground network, using beamformers, recovers user data streams transmitted by the user terminals from return downlink signals. The ground network, using beamformers generates forward uplink signals from appropriately weighted combinations of user data streams that, after relay by the end-end-end relay, produce forward downlink signals that combine to form user beams.

Abstract: A method enables communication between a process client and a wireless process server to carry out an area-specific process in an area. The method includes a step of transmitting a message from a wireless process server to a wireless communication device operated by the process client. The message includes information related to the area-specific process for enabling the process-client to better arrange time before the area-specific process is scheduled to carry out in the area. In a specific embodiment, the wireless communication server sends a message to notify the process client about a location and an estimate time for the process client to carry out the area-specific process. In another preferred embodiment, the communication system enables the process client to employ a wireless communication device owned by the process client.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing the execution of the operations of a neural network. One of the methods includes obtaining data representing a graph characterizing a plurality of operations of a neural network, wherein each node of the graph characterizes an operation of the neural network and each edge of the graph characterizes data dependency between the operations; processing the data representing the graph using a graph embedding neural network to generate an embedding of the graph; and processing the embedding of the graph using a policy neural network to generate a task output, wherein the task output comprises, for each of the plurality of operations of the neural network, a respective decision for a particular optimization task.

Abstract: A computer-implemented method of detecting one or more objects in a driving environment located externally to a vehicle, and a vehicle imaging system configured to detect one or more objects. The computer-implemented method includes training a first neural network to detect objects in a color video stream, the first neural network having a plurality of mid-level color features at a plurality of scales, and training a second neural network, operatively coupled to color neural network and an infrared video stream, to match, at the plurality of scales, mid-level infrared features of the second neural network to mid-level color features of the first neural network. A pixel-level invisibility map is then generated from the color video stream and the infrared video stream by determining differences, at each of the plurality of scales, between mid-level color features at the first neural network and mid-level infrared features at the second infrared neural network, and coupling the result to a fusing function.

Abstract: An attention mechanism-based 12-lead electrocardiogram (ECG) classification method is described, the method including acquiring an original image of a 12-lead ECG, segmenting waveform data recorded in the original image to obtain segmented waveform data for each lead in the 12-lead ECG, performing depth feature extraction on the segmented waveform data of said each lead to obtain a first feature map of said each lead, performing feature transformation on the first feature map of said each lead based on an attention mechanism to obtain a depth feature of said each lead, and classifying the depth feature of said each lead to obtain a classification result for the original image. The classification method can make full use of the 12-lead ECG for overall classification and improve the accuracy of image classification.

Abstract: According to one embodiment, a file transmission/reception device includes a communication direction managing unit and an application unit. The communication direction managing unit, in near field communication, cuts off a connection with an opposing device in a case where a conflict occurs with the opposing device, and, after being reconnected to the opposing device, switches the file transmission/reception device to any one mode of a master mode and a slave mode. The application unit performs transmission, reception, or transmission/reception of a file between the opposing device and the file transmission/reception device in the master mode or the slave mode in accordance with a mode specified by the communication direction managing unit.

Abstract: Methods and devices for offloading and/or aggregation of resources to coordinate uplink transmissions when interacting with different schedulers are disclosed herein. A method in a WTRU incudes functionality for coordinating with a different scheduler for each eNB associated with the WTRU's configuration. Disclosed methods include autonomous WTRU grand selection and power scaling, and dynamic prioritization of transmission and power scaling priority.

Abstract: Systems, devices, methods for capsule endoscopy procedures are disclosed. A system for a capsule endoscopy procedure includes a capsule device configured to capture in-vivo images over time of at least a portion of a gastrointestinal tract (GIT) of a person, a wearable device configured to be secured to the person where the wearable device is configured to receive at least some of the in-vivo images from the capsule device and to communicate at least some of the received images to a communication device at a same location as the wearable device, and a storage medium storing machine-executable instructions configured to execute on a computing system remote from the location of the wearable device. The instructions, when executed, cause the computing system to receive communicated images from the communication device, perform processing of the communicated images received from the communication device, and communicate with at least one healthcare provider device.