A method for planning sample points for surveying and mapping is disclosed, which includes: acquiring a reference photographing location point corresponding to a region to be surveyed and mapped, and establishing a mapping relation between one shooting point in a combined shooting point set and the reference photographing location point; determining a plurality of auxiliary photographing location points corresponding to the reference photographing location point based on the mapping relation preset relative positional relations between the shooting points in the combined shooting point set; and using the reference photographing location point and the plurality of auxiliary photographing location points as sample points for surveying and mapping based on which an unmanned aerial vehicle for surveying and mapping performs surveying and mapping in the region to be surveyed and mapped. An apparatus for planning sample points for surveying and mapping, a control terminal, and a storage medium are also disclosed.

A method is for generating element templates for forming templates when checking value documents of a specified value document type having at least two specified manufacturing elements, which, where applicable, partially overlap each other, and the element templates correspond to the manufacturing elements. Digital training images of training value documents of the specified value document type and a digital reference image of a reference value document of the specified value document type are used, which each have pixels to which pixel data are respectively assigned.

Methods, systems, articles of manufacture, and apparatus to recalibrate confidences for image classification are disclosed. An example apparatus to classify an image includes an image crop detector to detect a first image crop from the image, the first image crop corresponding to a first object, a grouping controller to select a second image crop corresponding to a second object at a location of the first object, a prediction generator to, in response to executing a trained model, determine a label corresponding to the first object and a confidence level associated with the label, and a confidence recalibrator to recalibrate the confidence level based on a probability of the first object having a first attribute based on the second object having a second attribute, the confidence level recalibrated to increase an accuracy of the image classification.

An information processing system including units configured to: acquire a pathologic tissue image of a patient having a target disease; divide the pathologic tissue image into region images; input each of the region images to each of a plurality of feature prediction models constructed one-to-one for types of histopathological features; sort a plurality of region images of which respective combinations of presence or absence of the histopathological features based on the acquisition match a previously set combination of presence or absence of the histopathological features at time of sorting; input each of the region images selected by the sorting to each of gene mutation prediction models constructed one-to-one for types of gene mutations, the gene mutation prediction models each having a combination of presence or absence of the histopathological features; and output a prediction result of presence or absence of at least one gene mutation in the patient.

The present invention provides a system and method to create a multi attribute based data synthesis. The method includes obtaining an input image, where the input image includes a human wearing an apparel in a foreground and a scene in a background, detecting the human in the input image, detecting a face region of the human in the input image, generating a body-ratio-heuristics for the input image, generating a set of mask labels associated with the input image, and performing a domain randomization of the input image to generate a plurality of images to create the image database.

A method of processing a vehicle image includes obtaining a first image from at least one vehicle exterior camera when a vehicle is in a first position. An obstructed area is identified in the first image. At least one previously captured image is obtained from the at least one vehicle exterior camera when the vehicle is in a second position different from the first position. An unobstructed area of the at least one previously captured image that corresponds to at least a portion of the obstructed area of the first image is identified. The unobstructed area is stitched into at least a portion of the obstructed area to create a corrected image that corresponds to the first image with at least a portion of the obstructed area removed. The corrected image is displayed on a display in the vehicle.

Some embodiments provide image evaluation systems and methods, comprising: a plurality of camera systems distributed about a retail facility and each of the plurality of camera systems; and an image processing system configured to receive multiple images over time, process each image comprising: determine, from pixel data, a gradient amplitude and directional component; determine a histogram curve from the gradient amplitudes as a function of the directional component of the pixel data, and identify a key direction relative to a maximum accumulation of the gradient amplitudes; for the gradient amplitudes, of the pixel data, having a corresponding directional component that is within a direction threshold of the key direction, identify a number of local maxima corresponding to the key direction; and determine a quantity of items of the product corresponding to a quantity of the number of local maxima.

A lane line detection method, an electronic device, and a storage medium, related to the field of artificial intelligence, and particularly related to computer vision and deep learning technologies, which can be applied to intelligent traffic scenes, are provided. The method includes: dividing an image into a foreground region and a background region; determining a solid line and a dotted line included in the foreground region; determining, according to the solid line and the dotted line comprised in the foreground region, whether a dotted-and-solid line is included in the foreground region; and determining a lane line detection result according to the solid line, the dotted line, and whether a dotted-and-solid line is comprised in the foreground region. According to the technical solution, the accuracy of lane line detection can be improved.

A method of measuring a critical dimension (CD) includes forming a plurality of patterns in a substrate, creating first to n-th images, where n is a natural number greater than 1, for first to n-th areas in the substrate, respectively, where the first to n-th areas do not overlap with each other, where each of the first to n-th areas comprising at least some of the plurality of patterns, creating a merged image for the first to n-th images, and measuring a CD for a measurement object from the plurality of patterns using the merged image. The merged image has a higher resolution than each of the first to n-th images.

Disclosed is a method and an order generation system for a software interface, the method including: by a UE, collecting operation information about a target object, and determining an operation type and an operation coordinate of the target object on the software interface; acquiring a coordinate set in a price coordinate system of the software interface;

calculating differences between the operation coordinate and the plurality of coordinate values to obtain a plurality of difference values, extracting a minimum difference value from the plurality of difference values, and obtaining a first price corresponding to the minimum difference value; and generating a first straight line matching the first price and the operation type, and sending a transaction request including the first price and the operation type to a background server after superimposing the first straight line onto the software interface.