Abstract: A system generates applications based on a domain specific language (DSL). The applications allow a user to take measurements based on user movements using a client device (for example, a mobile phone) for providing to an expert. The domain specific language includes commands that cause the generated applications to perform various tasks, such as providing specific instructions to the user, starting and stopping recording, taking measurements, and so on. The system compiles the DSL specification to generate executable instructions that are deployed (for example, on a client device such as a mobile phone). The DSL specification allows users to specify virtual points based on multiple landmarks obtained from the images of the user. The DSL specification allows users to specify a point as a stable point for landmarks that are expected to be stationary but move across frames.

Abstract: A three-dimensional data decoding method includes: selecting, from among contexts, a first context for an encoded first information item to be processed; and arithmetic-decoding the encoded first information item to be processed, using the first context, to generate a first information item to be processed. Encoded first information items including the encoded first information item to be processed are included in a bitstream generated by encoding an information item about positions of three-dimensional points. The encoded first information items are generated by arithmetic-encoding first information items including the first information item to be processed. The first information items each correspond to a different one of reference positions and indicate whether a three-dimensional point corresponding to a reference position corresponding to the first information item is present.

Abstract: The present disclosure is related to imaging systems and methods. The method includes obtaining optical image data of a subject to be scanned by a medical device. The method includes determining a scan range of the subject based on the optical image data. The scan range includes at least one scan area of the subject. The method includes determining at least one parameter value of at least one scan parameter based on the at least one scan area of the subject. The method further includes causing the medical device to scan the subject based on the scan range and the at least one parameter value of the at least one scan parameter.

Abstract: Systems and methods for estimating optimal gantry orientation and/or scanning parameters using image(s) from one or several cameras for a CT scan of a patient. Images are acquired of a patient. An optimal gantry tilt is estimated that keeps the patient's eye lenses outside a range of a beam during the scan. The CT scan is performed using the optimal gantry tilt. A scout scan is not used.

Abstract: An imaging chamber configured to receive a flow of a fluid sample is provided. The imaging chamber includes a reservoir and an imaging window. The reservoir includes a contrast-enhancing agent and is configured to receive the flow of the fluid sample. The imaging window of the imaging chamber is downstream from the reservoir.

Abstract: An image processing apparatus configured to perform recognition processing for a target object in an input image, includes at least one memory storing a program, and at least one processor. The processor, by executing the program, causes the image processing apparatus to perform the recognition processing for the target object in a first image having a first resolution acquired based on the input image and acquire a first recognition result, determine whether or not a reliability of the first recognition result satisfies a predetermined standard, and perform the recognition processing for the target object in a second image which has a higher resolution than the first resolution acquired based on the input image, and acquire a second recognition result, in a case where it is determined that the reliability of the first recognition result does not satisfy the predetermined standard.

Abstract: Systems and methods are provided to perform measurements of vibratory motion in three axes using two or more cameras. The cameras are mounted in a fixed spatial relationship to each other and are calibrated such that internal camera distortion and external camera coordinate transformations are determined. Data from each pair of cameras can be processed independently to determine the z-axis motion from changes in the x-axis and y-axis motion measured by the cameras. Measurement noise can impact the small differences in values from camera pairs and multiple techniques have been identified to reduce noise and make reliable measurements of the z-axis vibratory motion. If more than two cameras are utilized, then the data from each pair can be averaged to improve the measured values.

Abstract: The present disclosure discloses an image denoising method, an electronic device and a storage medium, the method including: acquiring a preset quantity of full dose images and low dose images; training a preset deep learning model according to the full dose images and the low dose images, wherein the deep learning model includes a multi-frequency band denoising network, and the multi-frequency band denoising network includes one multi-frequency band separation module, N denoising modules and one summation module; and acquiring an image to be denoised, and denoising the image to be denoised through the multi-frequency band denoising network in a trained deep learning model.

Abstract: In various examples, techniques for multi-dimensional tracking of objects using two-dimensional (2D) sensor data are described. Systems and methods may use first image data to determine a first 2D detected location and a first three-dimensional (3D) detected location of an object. The systems and methods may then determine a 2D estimated location using the first 2D detected location and a 3D estimated location using the first 3D detected location. The systems and methods may use second image data to determine a second 2D detected location and a second 3D detected location of a detected object, and may then determine that the object corresponds to the detected object using the 2D estimated location, the 3D estimated location, the second 2D detected location, and the second 3D detected location. The systems and method then generate, modify, delete, or otherwise update an object track that includes 2D state information and 3D state information.

Abstract: Described herein is a method, and system for training a deblurring model and deblurring an image (e.g., SEM image) of a patterned substrate using the deblurring model and depth data associated with multiple layers of the patterned substrate. The method includes obtaining, via a simulator using a target pattern as input, a simulated image of the substrate, the target pattern comprising a first target feature to be formed on a first layer, and a second target feature to be formed on a second layer located below the first layer; determining, based on depth data associated with multiple layers of the substrate, edge range data for features of the substrate; and adjusting, using the simulated image and the edge range data associated with the target pattern as training data, parameters of a base model to generate the deblurring model to a deblur image of a captured image.

Abstract: A method for detecting obstacles implemented in an electronic device includes obtaining detection point data from at least one sensor, the detection point data comprising a first position coordinate of each of a plurality of detection points; transforming the first position coordinate of each of the plurality of detection points to a second position coordinate of each of the plurality of detection points relative to an ego vehicle; determining at least one target object according to a plurality of second position coordinates; calculating target object data of the at least one target object according to a second position coordinate of each of the plurality of detection points relative to the ego vehicle; tracking the at least one target object according to the target object data.

Abstract: A method of verifying multi-modal medical data is proposed. The method comprises: accessing multi-modal medical data of a subject, the multi-modal medical data comprising a medical image of a specimen slide, wherein a specimen in the specimen slide was collected from the subject; generating a prediction pertaining to a biological attribute of the medical image based on the medical image; determining a degree of consistency between the biological attribute of the medical image and other modalities of the multi-modal medical data; and outputting, based on the degree of consistency, an indication of whether the multi-modal medical data contain inconsistency.

Abstract: A work machine management system includes an acquisition unit configured to acquire posture information indicating a posture of a driver of a work machine when boarding and alighting, a transmission unit configured to transmit the posture information to an outside of the work machine, and a determination unit configured to determine appropriateness of the posture when boarding and alighting based on the received posture information.

Abstract: Disclosed is a method for capturing a motion trajectory of a to-be-rendered virtual object, rendering a virtual object, and drawing a tracking primitive, including. determining at least one tracking primitive corresponding to a to-be-rendered virtual object in a virtual scene based on the to-be-rendered virtual object, the tracking primitive corresponding to the to-be-rendered virtual object covering a movable part of the to-be-rendered virtual object; drawing the tracking primitive corresponding to the to-be-rendered virtual object in the virtual scene; and capturing the motion trajectory of the to-be-rendered virtual object in the virtual scene based on a motion trajectory corresponding to the drawn tracking primitive.

Abstract: A system with a processing unit for processing X-ray images may be utilized for assisting in humerus surgery based on X-ray images. Firstly, at least two X-ray images are received having been generated with different imaging directions and showing a proximal portion of a humerus. Then, (i) the X-ray images are registered, (ii) an approximation of at least a part of the 2D outline of the humerus head in both images is determined, (iii) a 3D approximation of the humerus head based on the approximated 2D outlines and the registered images is determined, and (iv) 2D image coordinates of a total of at least three different points in the X-ray images are determined. Finally, an approximation of an anatomical neck is determined as a curve on the 3D approximation of the humerus head based on the at least three determined points.

Abstract: The present disclosure relates to an image scanning method and system for a medical device. The method may include determining a target position of a scanned object in a scanning region of the medical device; moving the scanned object to the target position. The method may include controlling the medical device to perform a scanning on the scanned object to obtain a scanned image of the scanned object. The method may include determining at least one abnormal point in the scanned image and recommending a scanning protocol based on the at least one abnormal point. The method may further include controlling the medical device to perform a scanning on the scanned object based on the scanning protocol.

Abstract: Embodiments of the present disclosure provide a plane estimation method and apparatus, an electronic device and a storage medium. The method includes: obtaining multiple video frames of a target video, extracting feature points from each of the multiple video frames, determining multiple same feature points in feature points of the multiple video frames, and determining position information of the multiple same feature points in the multiple video frames; determining a homography matrix of a plane between two adjacent video frames according to the position information of the multiple same feature points in the multiple video frames based on a random sample consensus algorithm; and determining parameter information of the plane between the two adjacent video frames according to the homography matrix of the plane.

Abstract: A system may receive, via a first user interface associated with an online marketplace, a multi-modality request to retrieve a listing for an item, the multi-modality request comprising at least a first image and a first natural language text associated with the item. The system may generate an item embedding based on inputting the first image and the first natural language text to a machine learning model and may generate a first vector associated with the first image and the first natural language text included in the multi-modality request. The system may cause presentation, via the first user interface associated with the online marketplace, of one or more listings for the item retrieved based at least in part on a similarity metric between the first vector and a second vector of a plurality of vectors associated with a plurality of listings.

Abstract: A method and system of image processing for action classification uses fine-grained motion-attributes.

Abstract: Provided are methods, systems, and computer program products for image based LiDAR-camera synchronization. An example method may include: obtaining an image from an image sensor; detecting at least one edge of a pattern in the image, the pattern corresponding to at least one electromagnetic wave emitted from a rangefinder system; determining an offset between the pattern and the image based on the at least one edge of the pattern; determining the offset satisfies a synchronization threshold; and based on the determining the offset satisfies a synchronization threshold, adjusting a synchronization parameter of the image sensor or rangefinder system.