Abstract: Disclosed is a method of classifying a document for a straight-through processing (STP) using memory enabled modelling. The method includes receiving, performing a content extraction from the input image, and selecting a template with the highest matching probability from a database. The method further includes postprocessing the extracted content based on the predicted template and validating the extracted content. Thereafter, the method includes classifying the document for the STP if the extracted content is successfully validated corresponding to each of the image quality validation, the refined content extraction validation, and the layout validation.

Abstract: A system to extract data from regions of interest on a document is provided. The system includes a storage device storing an image derived from a document having text information. The system includes a document importer operable to perform optical character recognition to convert image data in the image to machine readable data. The system includes a neural network that identifies at least one region of interest on the image to classify an area of the at least one region of interest as a table. The neural network is operable to take as input the machine readable data and the image and combine both the machine readable data and the image to determine that the classified area is the table.

Abstract: A system to classify image of a document using neural network architecture is provided. The system includes a storage device storing the image derived from the document having text information. The system includes a document importer operable to perform optical character recognition to convert image data in the image to machine readable data. The system includes a neural network that perform semantic enrichment and positional context for the terms of interest present in the image. The neural network is configured to take as input the machine-readable data and the image and combine both the machine-readable data and the image to classify the image of the document based on the positional context of the terms of interest.

Abstract: A system to extract data from regions of interest on a document is provided. The system includes a storage device storing an image derived from a document having text information. The system includes a document importer operable to perform optical character recognition to convert image data in the image to machine readable data. The system includes a neural network that identifies at least one region of interest on the image to classify an area of the at least one region of interest as a table. The neural network is operable to take as input the machine readable data and the image and combine both the machine readable data and the image to determine that the classified area is the table.