Example embodiments that analyze images to characterize aspects of the images rely on a same neural network to characterize multiple aspects in parallel. Because additional neural networks are not required for additional aspects, such an approach scales with increased aspects.

A User Interface (UI) interface object detection system employs an initial dataset comprising a set of images, that may include synthesized images, to train a Machine Learning (ML) engine to generate an initial trained model. A data point generator is employed to generate an updated synthesized image set which is used to further train the ML engine. The data point generator may employ images generated by an application program as a reference by which to generate the updated synthesized image set. The images generated by the application program may be tagged in advance. Alternatively, or in addition, the images generated by the application program may be captured dynamically by a user using the application program.

A User Interface (UI) interface object detection system employs an initial dataset comprising a set of images, that may include synthesized images, to train a Machine Learning (ML) engine to generate an initial trained model. A data point generator is employed to generate an updated synthesized image set which is used to further train the ML engine. The data point generator may employ images generated by an application program as a reference by which to generate the updated synthesized image set. The images generated by the application program may be tagged in advance. Alternatively, or in addition, the images generated by the application program may be captured dynamically by a user using the application program.

A system can merge text bounding boxes such as Optical Character Recognition (OCR) bounding boxes. A document can comprise a plurality of the text bounding boxes. Distance thresholds between text bounding boxes can be utilized for comparison against a distance threshold. Distance thresholds can vary depending on context information associated with the document. In response to a determination that text bounding boxes satisfy the distance threshold, the text bounding boxes can be assigned to a bounding box group.

Herein is a probabilistic indexing technique for searching semi-structured text documents in columnar storage formats such as Parquet, using columnar input/output (I/O) avoidance, and needing minimal storage overhead. In an embodiment, a computer associates columns with text strings that occur in semi-structured documents. Text words that occur in the text strings are detected. Respectively for each text word, a bitmap, of a plurality of bitmaps, that contains a respective bit for each column is generated. Based on at least one of the bitmaps, some of the columns or some of the semi-structured documents are accessed.

The present application discloses a method and apparatus for digitizing paper data, an electronic device and a storage medium, relating to fields of image processing and cloud computing, in particular to image recognition technologies. The method includes: determining a standard template according to an image to be processed and mark information corresponding to the image to be processed, wherein the image to be processed is obtained by photographing paper data and the standard template is used to represent a reference coordinate system of the image to be processed; recognizing graphic handwriting information comprised in the image to be processed; and generating digitized data corresponding to the image to be processed according to the graphic handwriting information and the standard template.

A system can merge text bounding boxes such as Optical Character Recognition (OCR) bounding boxes. A document can comprise a plurality of the text bounding boxes. Distance thresholds between text bounding boxes can be utilized for comparison against a distance threshold. Distance thresholds can vary depending on context information associated with the document. In response to a determination that text bounding boxes satisfy the distance threshold, the text bounding boxes can be assigned to a bounding box group.

In aspects, the present invention discloses a method of configuring devices of a control system in a plant using a configuration server. The method comprises importing an engineering graphic object, detecting a plurality of textual elements and graphic elements, identifying a set of textual elements and a set of graphic elements as legends, associating the set of graphic elements with corresponding textual elements and the set of textual elements with a corresponding graphic elements, updating a symbol vocabulary and a device label vocabulary using the set of graphic elements and the set of textual elements, associating one or more graphic elements and one or more textual elements from the plurality of graphic elements and the plurality of textual elements with corresponding devices, determining control information of a device based on the associated graphic elements and associated textual elements, and generating a plurality of engineering artifacts based on the control information.

An image processing apparatus is provided. The image processing apparatus includes a data receiver, an image specifier, a replacement specifier, and a data generator. The data receiver receives data. The image specifier specifies a first image contained in the data. The replacement specifier specifies replacement data for the first image on the basis of a characteristic of the data. The data generator generates data in which the first image has been replaced with an image represented by the replacement data.

Aspects of the present invention disclose a method for extracting information of an unlabeled image within a document and aligning the information to text of the document. The method includes one or more processors identifying an image that is not associated with a corresponding label in a document that includes text. The method further includes determining a feature of an object of the image. The method further includes identifying an alignment candidate of the text of the document based at least in part on the feature of the object, wherein the alignment candidate is a segment of the text of the document identified as corresponding to the feature of the object. The method further includes aligning the feature with the alignment candidate of the text of the document.