An object is to provide a polygon detection device, a polygon detection method, and a polygon detection program to accurately detect a polygon resembling a reference polygon from an image. The polygon detection device acquires a ratio among lengths of sides of a reference polygon included in an appearance of a predetermined object. The polygon detection device acquires a photographic image of the predetermined object. The polygon detection device detects line segments from the acquired photographic image. The polygon detection device forms at least one polygon based on the detected line segments. The polygon detection device identifies, from the formed polygon, a polygon corresponding to the reference polygon based on a degree of similarity between a ratio among lengths of sides of the formed polygon and the acquired ratio among the lengths of sides of the reference polygon, among from the formed polygon.

In a method for processing a document image, a document image to be processed is acquired. Text nodes of multiple granularities, visual nodes of multiple granularities, respective node information of the text nodes, and respective node information of the visual nodes in the document image are obtained. A multi-granularity and multi-modality document graph is construct based on the text nodes of multiple granularities, the visual nodes of multiple granularities, the respective node information of the text nodes and the respective node information of the visual nodes. Multi-granularity semantic feature information of the document image is determined based on the multi-granularity and multi-modality document graph, the respective node information of the text nodes and the respective node information of the visual nodes.

Systems and methods for providing a threat intelligence system include a system provider device that downloads, through communication over a network and from one or more targeted websites, a plurality of images of a first environment. Based on an OCR process, the system provider device may extract a set of textual data corresponding to a subset of images of the plurality of images, where the subset of images depict text. The system provider device stores the set of textual data in an indexed and searchable database. The system provider device assigns a threat assessment score to each image based on the set of textual data, and the threat assessment score may be updated based on comparison of the set of textual data with other sets of textual data. Based on the threat assessment score being greater than a threshold value, the system provider device may generate a security alert.

Systems and methods for providing a threat intelligence system include a system provider device that downloads, through communication over a network and from one or more targeted websites, a plurality of images of a first environment. Based on an OCR process, the system provider device may extract a set of textual data corresponding to a subset of images of the plurality of images, where the subset of images depict text. The system provider device stores the set of textual data in an indexed and searchable database. The system provider device assigns a threat assessment score to each image based on the set of textual data, and the threat assessment score may be updated based on comparison of the set of textual data with other sets of textual data. Based on the threat assessment score being greater than a threshold value, the system provider device may generate a security alert.

A method for recognizing a text, an electronic device and a storage medium. An implementation of the method comprises: obtaining a multi-dimensional first feature map of a to-be-recognized image; performing, based on feature values in the first feature map, feature enhancement processing on each feature value in the first feature map; and performing a text recognition on the to-be-recognized image based on the first feature map after the enhancement processing.

Methods, systems, articles of manufacture and apparatus are disclosed to label text on images. An example apparatus includes colorizer circuitry to apply color to text boxes corresponding to optical character recognition (OCR) data associated with an image, OCR manager circuitry to render an OCR text prompt associated with the OCR data, the OCR text prompt to be rendered proximate to respective ones of the text boxes, the OCR text prompt to display a text portion of the OCR data, and edit circuitry to (a) render an interface in response to selection of the OCR text prompt, the interface populated with the text portion of the OCR data, and (b) in response to an overwrite input to the interface, update the text portion of the OCR data in a memory corresponding to the image.

The disclosure relates to apparatuses and methods for detecting elements of an assembly, such as electrical components in a printed circuit board. First and second artificially intelligent classifiers are provided for detecting elements in a high-resolution image of the assembly, wherein the first artificially intelligent classifier is pre-trained to detect first elements and the second artificially intelligent classifier is pre-trained to detect second elements, each of the first elements having a size within a first size range, and each of the second elements having a size within a second size range, in which the first size range includes elements having a size that is greater than the size of elements included within the second size range. The second artificially intelligent classifier can be prevented from subsequently searching for elements within bounding boxes previously obtained by the first artificially intelligent classifier.

A system may iteratively scan a portion of a document, extract first data from the portion of the document, and determine, using a trained model, whether the first data corresponds to one or more document types based on one or more confidence thresholds. The system may repeat this process, increasing the portion of the document scanned by a predetermined amount each iteration, until the first data corresponds to the one or more document types based on the one or more confidence thresholds. Responsive to determining the first data corresponds to the one or more document types based on the one or more confidence thresholds, the system may cause a graphical user interface (GUI) of a user device to display a notification indicating a document type match.

A system may iteratively scan a portion of a document, extract first data from the portion of the document, and determine, using a trained model, whether the first data corresponds to one or more document types based on one or more confidence thresholds. The system may repeat this process, increasing the portion of the document scanned by a predetermined amount each iteration, until the first data corresponds to the one or more document types based on the one or more confidence thresholds. Responsive to determining the first data corresponds to the one or more document types based on the one or more confidence thresholds, the system may cause a graphical user interface (GUI) of a user device to display a notification indicating a document type match.

A system for generating textual instructions for manufacturers from hybrid textual and image data includes a manufacturing instruction generator that may generate a language processing module from a first training set including at least a training annotated file describing at least a first product to manufacture, the at least an annotated file containing one or more textual data, and at least an instruction set containing one or more manufacturing instructions to manufacture the at least a first product. Manufacturing instruction generator may use the language processing to generate textual instructions for manufacturers from at least an annotated file and may initiate manufacture using the generated manufacturing instructions.