Embodiments of the invention are directed to systems, methods, and computer program products for a unique platform for analyzing, classifying, extracting, and processing information from graphical representations. Embodiments of the inventions are configured to provide an end to end automated solution for extracting data from graphical representations and creating a centralized database for providing graphical attributes, image skeletons, and other metadata information integrated with a graphical representation classification training layer. The invention is designed to receive a graphical representation for analysis, intelligently identify and extract objects and data in the graphical representation, and store the data attributes of the graphical representation in an accessible format in an automated fashion.

Methods, systems and apparatus, including computer programs encoded on computer storage media for determining a center location of a ground control point used in aerial surveys. Machine learning models are used to identify in digital images pixel coordinates of the ground control point identified in the digital images. These image pixel coordinates are used in photogrammetric processing and software.

The present disclosure provides a tissue density analysis system. The system includes an acquisition module configured to obtain image data and tissue density distribution data; a display module configured to display the obtained tissue density distribution data in one or more charts; a processing module configured to adjust the tissue density distribution data displayed in the one or more charts; and a storage module configured to store the image data, the tissue density distribution data and an instruction.

An article of manufacture may include a matrix barcode on a physical medium and associated with an environment. The matrix barcode may include a plurality of colors, where at least one of the plurality of colors is a least prevalent color, of a plurality of prevalent colors in the environment.

Methods, systems, and apparatus, including medium-encoded computer program products, for pre-processing image data before 3D object tracking include, in at least one aspect, a method including: performing object detection in uncompressed, two-dimensional image data from a camera to produce two-dimensional location data for objects of interest; processing the two-dimensional location data for the objects of interest using a motion criterion to generate possible paths data for the objects of interest; and constructing a flight track of an object in three-dimensional space, from the possible paths data and position information obtained from a sensor, by filtering out false positives in the possible paths data.

The disclosed computer-implemented method may include generating a three-dimensional (3D) feature map for a digital image using a fully convolutional network (FCN). The 3D feature map may be configured to identify features of the digital image and identify an image region for each identified feature. The method may also include generating a region composition graph that includes the identified features and image regions. The region composition graph may be configured to model mutual dependencies between features of the 3D feature map. The method may further include performing a graph convolution on the region composition graph to determine a feature aesthetic value for each node according to the weightings in the node's weighted connecting segments, and calculating a weighted average for each node's feature aesthetic value to provide a combined level of aesthetic appeal for the digital image. Various other methods, systems, and computer-readable media are also disclosed.

A digital image sequence with multiple image frames can be enhanced. An appearance graph can be determined from the digital image sequence. The appearance graph includes prime layer nodes. Each prime layer node can represent a distinctive visual style. A prime layer image sequence can be computed for each prime layer node that matches the visual style represented by the prime layer node. An enhanced image sequence can be generated by blending at least two prime layer image sequences as defined by the appearance graph.

A method includes generating a depth map of a real environment as seen from a viewpoint that comprises pixels having corresponding depth values of one or more physical objects. Based on the depth map a two-dimensional occlusion surface is generated representing at least a visible portion of the one or more physical objects that are located within a predetermined depth range defined relative to the viewpoint. The two-dimensional occlusion surface is posed in a three-dimensional coordinate system such that the two-dimensional occlusion surface is located at a predetermined distance from the viewpoint. The visibility of a virtual object is determined relative to the one or more physical objects by comparing a model of the virtual object with the two-dimensional occlusion surface, and an output image is generated based on the visibility of the virtual object.

Provided herein are methods and systems for making patient-specific therapy recommendations of a combination of any two or more therapies selected from a lipid-lowering therapy, an anti-inflammatory therapy for patients with known or suspected cardiovascular disease, such as atherosclerosis.

A method of digitally processing a plurality of pixels of an image captured using an array of sensing pixels of an optical sensor device. The method comprises identifying a measurement pixel of the plurality of pixels corresponding to a measurement point on a target to be measured. The method then comprises identifying a number of pixels of the plurality of pixels neighbouring the measurement pixel, the number of pixels having a number of intensity values, respectively. A curve is then fitted to the number of pixels and the number of respective intensity values. An estimated intensity value is then determined from the curve in respect of the measurement pixel, thereby simulating a predetermined field of view in respect of the measurement pixel narrower than an actual field of view of the measurement pixel.