Abstract: Embodiments herein provide for a method of determining an optical device modulation transfer function (MTF). The method described herein includes projecting a baseline image of a pattern from a light engine to a detector. The baseline image is analyzed to determine a baseline function. A baseline fast Fourier transform (FFT) or a baseline MTF of the baseline function is obtained. The method further includes projecting an image of the pattern from the light engine to one or more optical devices. The pattern is outcoupled from the one or more optical devices to the detector. The image is analyzed to determine a function. A function FFT or a function MTF is obtained corresponding to the image. An optical device MTF of the one or more optical devices is determined by comparing the baseline FFT and the function FFT determined by analyzing the image or by comparing the baseline MTF and the function MTF determined by analyzing the image.

Abstract: A rendered image is generated from a semiconductor device design file. The rendered image is segmented based on a grey level of the rendered image. Care areas are determined based on the segmenting. Defect inspection is performed in the care areas. This process can be performed on a wafer inspection tool that uses photon optics or electron beam optics.

Abstract: Described is determining defects of an object produced using an additive manufacturing process, including: determining spatially resolved first data relating to n objects, the first data defines a process coordinate system for each of the n objects, determining measurement data relating to the n objects by imaging the n objects, the measurement data defines, for each of the n objects, an object representation in a measurement coordinate system, determining which coordinates of at least one section of the measurement coordinate system are defect coordinates assigned to a defect in the object representation; correlating the at least one section with a corresponding section of the process coordinate system in order to collect training data, training an adaptive algorithm for determining defect coordinates in spatially resolved data, by means of the training data, determining spatially resolved second data, and analysing the second data for defects by means of the adaptive algorithm.

Abstract: A controller obtains plural images generated by an imaging device disposed onboard a vehicle, and analyzes at least first and second images of the plural images to identify a feature of interest that is offboard the vehicle and at least partially depicted in the first and second images. The controller determines a first unit vector for the feature of interest based on a first location of the feature of interest in the first image, and determines a second unit vector for the feature of interest based on a second location of the feature of interest in the second image. The controller calculates a third location of the feature of interest, relative to a physical environment, based on the first unit vector, the second unit vector, and at least one of a first reference location of the vehicle or a second reference location of the vehicle.

Abstract: Systems and methods for generating a prediction of a body composition of a user using an image capturing device are disclosed. The systems and methods can be used to predict body compositions such as body fat percentage, water content percentage, muscle mass, bone mass, and so on, from a single user image. The methods include the steps of receiving one or more user images and one or more user parameters, generating one or more key points based on the one or more user images, and generating a prediction of the body composition of the user based on the one or more key points and the one or more user parameters, using a body composition deep learning network (DLN). In one embodiment, the body composition DLN comprises a face image DLN, a body feature DLN, and an output DLN.

Abstract: A weeding robot and a method and apparatus for planning a weeding path for the weeding robot and a medium are provided. The method for planning a weeding path for the weeding robot includes the following steps: acquiring an image segmentation model based on neural network model training, where the image segmentation model is configured to identify and segment a weed target feature, a soil target feature and a crop target feature; and based on the weed target feature, acquiring the weed target feature by intra-camera tracking, and acquiring the weed target feature by inter-camera tracking, and planning a weeding path for a weeding robotic arm of the weeding robot, to enable the weeding robotic arm to weed according to the weeding path.

Abstract: Disclosed herein is a method to disentangle linear-encoded facial semantics from facial images without external supervision. The method uses linear regression and sparse representation learning concepts to make the disentangled latent representations easily interpreted and manipulated. Generated facial images are decomposed into multiple semantic features and latent representations are extracted to capture interpretable facial semantics. The semantic features may be manipulated to synthesize photorealistic facial images by sampling along vectors representing the semantic features, thereby changing the associate semantics.

Abstract: An image processing device includes: a contribution ratio calculation unit that calculates a contribution ratio of a predetermined pixel or a predetermined region in depth calculation in each of a plurality of pixels or a plurality of regions included in an input image; and a correction unit that corrects a depth value of the predetermined pixel or the predetermined region based on the contribution ratio.

Abstract: Disclosed herein are system, method, and computer program product embodiments for optimizing the determination of a phenotypic impact of a molecular variant identified in molecular tests, samples, or reports of subjects by way of regularly incorporating, updating, monitoring, validating, selecting, and auditing the best-performing evidence models for the interpretation of molecular variants across a plurality of evidence classes.

Abstract: Objects are tracked in real time in a composed video acquired by joining a plurality of videos. A grouping candidate determining unit extracts objects present within an overlapping area, in which pieces of frame data are overlapped, among objects that have been detected and tracked in each of a plurality of pieces of frame data that were captured at the same time as candidate objects. A grouping unit arranges a plurality of candidate objects of which a degree of overlapping is equal to or larger than a predetermined threshold as a group, and an integration unit assigns integration object IDs to groups and objects that have not been grouped.

Abstract: A method and a device for determining an extraction model of a green tide coverage ratio based on mixed pixels. The method includes acquiring sample truth values respectively corresponding to a plurality of target regions water body and green tide; acquiring a plurality of first remote sensing data of a first satellite sensor, the plurality of remote sensing data are in one-to-one correspondence with the plurality of target regions; determining reflection index sets respectively corresponding to the plurality of target regions according to the plurality of remote sensing data; and determining the extraction model of the green tide coverage ratio corresponding to the first satellite sensor according to the sample truth value corresponding to each of the plurality of target regions and the reflection index set corresponding to each of the plurality of target regions.

Abstract: A system and method include obtaining and authenticating image files from users such as insured users at the request of an entity such as an insurance provider. The requesting entity may supply an electronic address of the user and a unique identifier. The system may transmit a link to the electronic address. When selected, the link causes an image authentication application to be installed on a user device. The application takes the images securely and separately from a native camera application. Each image authentication application may be customized for each requesting entity. The authentication server may identify the requesting entity that made the request and identify a corresponding image authentication application to be provided to the electronic address. The images from the image authentication application may be authenticated via reverse image search, time, geolocation, and/or other information. The authenticated images and/or related data may be provided to the requesting entity.

Abstract: A diagnostic tool for deep learning similarity models and image classifiers provides valuable insight into neural network decision-making. A disclosed solution generates a saliency map by: receiving a test image; determining, with an image classifier, an image classification of the test image; determining, for the test image, a first activation map for at least one model layer using the determined image classification; determining, for the test image, a first gradient map for the at least one model layer using the determined image classification; and generating a first saliency map as an element-wise function of the first activation map and the first gradient map.

Abstract: A LUS robotic surgical system is trainable by a surgeon to automatically move a LUS probe in a desired fashion upon command so that the surgeon does not have to do so manually during a minimally invasive surgical procedure. A sequence of 2D ultrasound image slices captured by the LUS probe according to stored instructions are processable into a 3D ultrasound computer model of an anatomic structure, which may be displayed as a 3D or 2D overlay to a camera view or in a PIP as selected by the surgeon or programmed to assist the surgeon in inspecting an anatomic structure for abnormalities. Virtual fixtures are definable so as to assist the surgeon in accurately guiding a tool to a target on the displayed ultrasound image.

Abstract: Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques including: obtaining input MR data obtained by imaging the subject using the MRI system; generating a plurality of transformed input MR data instances by applying a respective first plurality of transformations to the input MR data; generating a plurality of MR images from the plurality of transformed input MR data instances and the input MR data using a non-linear MR image reconstruction technique; generating an ensembled MR image from the plurality of MR images at least in part by: applying a second plurality of transformations to the plurality of MR images to obtain a plurality of transformed MR images; and combining the plurality of transformed MR images to obtain the ensembled MR image; and outputting the ensembled MR image.

Abstract: A method for estimating depth of a scene includes selecting an image of the scene from a sequence of images of the scene captured via an in-vehicle sensor of a first agent. The method also includes identifying previously captured images of the scene. The method further includes selecting a set of images from the previously captured images based on each image of the set of images satisfying depth criteria. The method still further includes estimating the depth of the scene based on the selected image and the selected set of images.

Abstract: A control section is included, the control section including an accumulation function of, when recognizing a specific user on a basis of sensor data acquired via an agent device, generating episode data in the accumulation section on a basis of a keyword extracted from the sensor data, generating a question for drawing out information concerning the episode data, and accumulating a reply from the specific user to the question in the episode data, and a responding function of, when recognizing the specific user on the basis of the sensor data acquired via the agent device, retrieving the episode data through the accumulation section on the basis of the keyword extracted from the sensor data, and generating response data concerning the retrieved episode data for the agent device to respond to the specific user.

Abstract: A manufacturing data analyzing method and a manufacturing data analyzing device are provided. The manufacturing data analyzing method includes the following steps. Each of at least one numerical data, at least one image data and at least one text data is transformed into a vector. The vectors are gathered to obtain a combined vector. The combined vector is inputted into an inference model to obtain a defect cause and a modify suggestion.

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for detecting and indicating modifications between a digital image and a modified version of a digital image. For example, the disclosed systems generates an ordered collection of change records in response to detecting modifications to the digital image. The disclosed systems generates determine one or more non-contiguous modified regions of pixels in the digital image based on the change records. The disclosed system generate an edited region indicator corresponding to the non-contiguous modified regions. The disclosed systems can further color-code the edited region indicator at an object level based on objects in the modified version of the digital image.

Abstract: Disclosed is an information processing device, comprising: acquisition circuitry configured to acquire image data including a frame; and index calculation circuitry configured to: determine an average value of the frame, and predict a signal-to-noise ratio of the image data based on the average value of the frame.