Abstract: An autoencoder may be trained to predict 3D pose labels using simulation data extracted from a simulated environment, which may be configured to represent an environment in which the 3D pose estimator is to be deployed. Assets may be used to mimic the deployment environment such as 3D models or textures and parameters used to define deployment scenarios and/or conditions that the 3D pose estimator will operate under in the environment. The autoencoder may be trained to predict a segmentation image from an input image that is invariant to occlusions. Further, the autoencoder may be trained to exclude areas of the input image from the object that correspond to one or more appendages of the object. The 3D pose may be adapted to unlabeled real-world data using a GAN, which predicts whether output of the 3D pose estimator was generated from real-world data or simulated data.

Abstract: Disclosed are devices, systems and methods for processing an image. In one aspect a method includes receiving an image from a sensor array including an x-y array of pixels, each pixel in the x-y array of pixels having a value selected from one of three primary colors, based on a corresponding x-y value in a mask pattern. The method may further include generating a preprocessed image by performing preprocessing on the image. The method may further include performing perception on the preprocessed image to determine one or more outlines of physical objects.

Abstract: A system, device and method of imaging using a real-time, AI-enabled analysis device coupled to an imaging device during an image scan of a subject includes: receiving data corresponding to a plurality of image frames from the imaging device and user input identifying a region of interest (ROI) in a first image frame; providing data corresponding to the first image frame, including the identified ROI and data corresponding to the remaining image frames to the AI-enabled data processing system; accepting a plurality of valid image frames from the plurality of image frames based on a predefined set of computer vision rules and a minimum accepted frame threshold; calculating, frame by frame, an ROI function value of the plurality of valid image frames; determining whether a predetermined ROI function value has been reached; and alerting an operator of the imaging device that the predetermined ROI function value has been reached.

Abstract: A method for estimating a region associated with a deformity on a surface portion of the skin of a mammal, the method comprising capturing a three-dimensional image of the surface portion to produce first data, the first data comprising depth data, and generating second data from the first data. The second data comprises curvature data. The method further comprises combining the first data and the second data to produce third data, and performing region growing on the third data.

Abstract: The present disclosure relates to a non-transitory computer-readable medium storing computer-executable instructions that, when executed, cause a processor to perform operations, including generating an imaging data set having both scan data and digitized biopsy data from a patient with small cell lung cancer (SCLC). Scan derived features are extracted from the scan data and biopsy derived features are extracted from the digitized biopsy data. A radiomic-pathomic risk score (RPRS) is calculated from one or more of the scan derived features and one or more of the biopsy derived features. The RPRS is indicative of a prognosis of the patient.

Abstract: An image sensor package, a system, and a method for counting fine particles by using a virtual grid line are provided. The image sensor package includes an image sensor array, a grid pattern layer formed on an outer area of the image sensor array and including a plurality of protruding patterns spaced apart from each other while protruding toward the central area of the image sensor array to form a virtual grid line, a dam pattern layer formed on the grid pattern layer, having a specific height, and configured to form a channel or a chamber for receiving the fine particles to be counted, and a cover glass formed on the dam pattern layer.

Abstract: Disclosed herein is a swappable modular-based radiofrequency (RF) frontend that is reconfigurable to form transmitting (TX) and receiving (RX) phased array systems for diverse applications. Such swappable RF frontend may be used with unique spatial and spectral optical processing of complex RF signals over an ultra-wide frequency band. The swappable RF front end may be used in conjunction with an optically upconverted imaging receiver and/or in conjunction with optically addressed phased array technologies transmitters.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for detecting and classifying an exposure defect in an image using neural networks trained via a limited amount of labeled training images. An image may be applied to a first neural network to determine whether the images includes an exposure defect. Detected defective image may be applied to a second neural network to determine an exposure defect classification for the image. The exposure defect classification can includes severe underexposure, medium underexposure, mild underexposure, mild overexposure, medium overexposure, severe overexposure, and/or the like. The image may be presented to a user along with the exposure defect classification.

Abstract: An improved convolution kernel system and method may be used to improve performance of analysis of input image data for autonomous or semi-autonomous vehicle navigation. A processing circuit may be used to apply a convolution kernel on the input data to provide output data that comprises output data segments. The application may include repeating scanning and summing, including parallel scanning input data segments of the different input channels and of the input data depth value to provide first intermediate results associated with the input data depth value, and summing first intermediate results associated with a same output data channel and with different input depth values to provide, per each output data channel, a second result. The output analyzed image data may be used to generate a vehicle control signal, such as automatic control of braking, acceleration, or steering of a vehicle.

Abstract: An embodiment object tracking method includes receiving a first image at time t from a camera, deriving a homography matrix based on the first image and a second image at time t?1, correcting a position of a first object detected from the second image using the homography matrix, detecting a second object matched with the first object from the first image, and tracking a change in position of the second object based on the corrected position of the first object.

Abstract: A method for processing microscope images in order to generate an image processing result comprises: implementing a convolutional neural network, wherein a first convolutional layer calculates an output tensor from an input tensor formed from a microscope image. The output tensor is input into one or more further layers of the convolutional neural network in order to calculate the image processing result. The first convolutional layer comprises a plurality of filter kernels. At least several of the filter kernels are respectively representable by at least one filter matrix with learning parameters and dependent filter matrices with implicit parameters, which are determined by means of the learning parameters and one or more weights to be learned, wherein the filter matrices with learning parameters of different filter kernels are different from one another and different layers of the output tensor are calculated by different filter kernels.

Abstract: If a configuration is employed in which modulation schemes used for an optical communication system can be switched depending on transmission conditions, the power consumption increases and the control becomes complex; therefore, an optical transmitter according to an exemplary aspect of the present invention includes an encoding means for encoding digital signals to be transmitted under a predetermined transmission condition over an optical carrier wave by using one of a plurality of encoding methods; an encoding control means for selecting a predetermined encoding method corresponding to the predetermined transmission condition from among the plurality of encoding methods and causing the encoding means to operate in accordance with the predetermined encoding method; a mapping means for mapping output bit signals output from the encoding means to modulation symbols; and an optical modulation means for modulating the optical carrier wave based on symbol signals output from the mapping means.

Abstract: A medical image processing method includes: determining a target mask of a target object in a medical image and a reference mask of a reference object in the medical image, the target mask indicating a position and a boundary of the target object, and the reference mask indicating a position and a boundary of the reference object; determining a feature size of the target object based on the target mask; determining a feature size of the reference object based on the reference mask; and determining a target size of the target object based on the feature size of the reference object, a preset mapping relationship between the feature size of the reference object and a reference size, and the feature size of the target object.

Abstract: A passenger vehicle optical communication system includes a source vehicle including a light source and an endpoint vehicle including a camera. The source vehicle transmits a series of patterns using the light source to communicate, as one example, state information to the endpoint vehicle.

Abstract: An image processing apparatus includes a planar distribution obtaining unit configured, using a plurality of radiation images captured using different radiation energies as input images, to obtain, by a sequential approximation solution by an iterative calculation, an output image representing a planar distribution for a substance contained in the input image. Based on a likelihood and a prior probability using one of a pixel value of a pixel of interest or a pixel value of a peripheral pixel as an input, the planar distribution obtaining unit decides the output image such that a probability that an output is a value of the planar distribution when an input is the input image that is maximized.

Abstract: One or more embodiments of the present disclosure may relate to communicating RADAR (RAdio Detection And Ranging) data to a distributed map system that is configured to generate map data based on the RADAR data. In these or other embodiments, certain compression operations may be performed on the RADAR data to reduce the amount of data that is communicated from the ego-machines to the map system.

Abstract: A method of determining a distribution of stem cells in a cell image, an electronic device and a storage medium are disclosed. The method acquires a cell image and segments the cell image and obtaining a plurality of sub-images. The plurality of sub-images is inputted into a stem cell detection model to detect to obtain a number of stem cells in each sub-image. A position of each sub-image in the cell image is determined. A distribution of the stem cells in the cell image is output, according to the number of stem cells in each sub-image and the position of each sub-image in the cell image. The present disclosure an accuracy of the distribution of stem cells in the cell image.

Abstract: The present application provides an optical network method and associated apparatus. The method includes: receiving uplink burst time assignment information; and enabling or disabling a laser module of a local end according to the uplink burst time assignment information.

Abstract: In a variety of embodiments, machine classifiers may model multi-turn dialogue as a one-to-many prediction task. The machine classifier may be trained using adversarial bootstrapping between a generator and a discriminator with multi-turn capabilities. The machine classifiers may be trained in both auto-regressive and traditional teacher-forcing modes, with the generator including a hierarchical recurrent encoder-decoder network and the discriminator including a bi-directional recurrent neural network. The discriminator input may include a mixture of ground truth labels, the teacher-forcing outputs of the generator, and/or noise data. This mixture of input data may allow for richer feedback on the autoregressive outputs of the generator. The outputs can be ranked based on the discriminator feedback and a response selected from the ranked outputs.

Abstract: A method for characterising an epicardial region using medical imaging data of a subject. The method comprises calculating the value of an epicardial radiomic signature of the epicardial region using the medical imaging data. Also disclosed is a method for deriving an epicardial radiomic signature indicative of cardiac health. The method comprises using a radiomic dataset to construct an epicardial radiomic signature. Also disclosed are systems for performing the aforementioned methods.