Provided are an information processing method and apparatus, an electronic device, and a storage medium. The method includes: acquiring an information processing application transmitted by a first client, and executing a predetermined command in accordance with a timer-based task mechanism to transmit a first prompt message for reviewing the information processing application to a second client; identifying, in response to an operation instruction on the second client, the information processing application as a target information processing application; acquiring an information processing request for the target information processing application transmitted by the first client in accordance with an asynchronous mechanism, and processing the information processing request; and feeding, in response to a polling initiated by the first client, a processing result of the information processing request back to the first client when the processing the information processing request is completed.

The technology disclosed processes input data through a neural network and produces an alternative representation of the input data. The input data includes per-cycle image data for each of one or more sequencing cycles of a sequencing run. The per-cycle image data depicts intensity emissions of one or more analytes and their surrounding background captured at a respective sequencing cycle. The technology disclosed processes the alternative representation through an output layer and producing an output and base calls one or more of the analytes at one or more of the sequencing cycles based on the output.

According to an embodiment, a reading system includes a first extractor and a reader. The first extractor extracts, from an image in which a meter is imaged, a first region surrounded with a first contour, and a second region surrounded with a second contour positioned outward of the first contour. The reader calculates a first indication based on the first region, calculates a second indication based on the second region, calculates a first score relating to the first indication based on the first region, and calculates a second score relating to the second indication based on the second region.

The invention discloses a method for glass detection in a real scene, which belongs to the field of object detection. The present invention designs a combination method based on LCFI blocks to effectively integrate context features of different scales. Finally, multiple LCFI combination blocks are embedded into the glass detection network GDNet to obtain large-scale context features of different levels, thereby realize reliable and accurate glass detection in various scenarios. The glass detection network GDNet in the present invention can effectively predict the true area of glass in different scenes through this method of fusing context features of different scales, successfully detect glass with different sizes, and effectively handle with glass in different scenes. GDNet has strong adaptability to the various glass area sizes of the images in the glass detection dataset, and has the highest accuracy in the field of the same type of object detection.

A computer-implemented method of using augmented reality (AR) to detect a plane and a spatial configuration of an object, the method comprising the steps of detecting one or more edges of the object; identifying one or more lines of the object; filtering the one or more lines of the object; iteratively approximating one or more distributions of the one or more lines; and determining boundaries of the object.

The technology disclosed relates to artificial intelligence based determination of analyte data for base calling. In particular, the technology disclosed uses input image data that is derived from a sequence of images. Each image in the sequence of images represents an imaged region and depicts intensity emissions indicative of one or more analytes and a surrounding background of the intensity emissions at a respective one of a plurality of sequencing cycles of a sequencing run. The input image data comprises image patches extracted from each image in the sequence of images. The input image data is processed through a neural network to generate an alternative representation of the input image data. The alternative representation is processed through an output layer to generate an output indicating properties of respective portions of the imaged region.

Disclosed are a method and apparatus for identifying versions of a form. In an example, clients of a medical company fill out many forms, and many of these forms have multiple versions. The medical company operates in 10 states, and each state has a different version of a client intake form, as well as of an insurance identification form. In order to automatically extract information from a particular filled out form, it may be helpful to identify a particular form template, as well as the version of the form template, of which the filled out form is an instance. A computer system evaluates images of filled out forms, and identifies various form templates and versions of form templates based on the images.

An example embodiment includes: a determination unit that, based on an image including an eye of a recognition subject, determines whether or not a colored contact lens is worn; and a matching unit that, when it is determined by the determination unit that the colored contact lens is worn, performs matching of the iris by using a feature amount extracted from a region excluding a predetermined range including an outer circumference of the iris out of a region of the iris included in the image.

A rail detecting device includes: a starting-region rail-starting-point redesignating unit that shifts a starting region for detecting rails to set a modified starting region and designates modified starting points of two rails at the lower edge of the modified starting region when portions of the two rails are not detected based on rail segments in an image; a rail-candidate detecting unit that detects multiple lines in the modified starting region as multiple modified rail candidates, the lines being candidates of edges of the two rails; a starting-region-rail assigning unit that assigns modified rail candidates whose lowest ends are closest to the corresponding modified starting points out of the multiple modified rail candidates as tentative modified rail segments; and a starting-region-rail disappearance determining unit that establishes the tentative modified rail segments as modified rail segments when distances between the lowest ends of the tentative modified rail segments.

A device for measuring the internal temperature of heap fermentation includes an infrared thermal imaging camera, a distance detection camera, and a controller. The infrared thermal imaging camera obtains a temperature distribution image of a surface of a fermentation heap. The distance detection camera obtains a distance between the surface of the fermentation heap and the distance detection camera. The controller matches the temperature distribution image of the surface of the fermentation heap with the distance between the surface of the fermentation heap and the distance detection camera, performs semantic segmentation on the image after matching is completed, extracts a three-dimensional (3D) contour temperature map of the surface of the fermentation heap, corrects a surface temperature of the fermentation heap, and predicts an estimated internal temperature of the fermentation heap, such that the internal temperature of the fermentation heap is effectively and accurately predicted.