Abstract: Systems and methods for automatic definition of natural language document classes. An example method comprises: producing, by a computer system, a plurality of image features by processing images of a plurality of documents; producing a plurality of text features by processing texts of a plurality of documents; producing a plurality of feature vectors, wherein each feature vector of the plurality of feature vectors comprises at least one of: a subset of the plurality of image features and a subset of the plurality of text features; clusterizing the plurality feature vectors to produce a plurality of clusters; defining a plurality of document categories, such that each document category of the plurality of document categories is defined by a respective feature cluster of the plurality of feature clusters; and training a classifier to produce a value reflecting a degree of association of an input document with one or more document categories of the plurality of document categories.

Abstract: A method includes obtaining an image of text. The text in the image includes one or more words in one or more sentences. The method also includes providing the image of the text as first input to a set of trained machine learning models, obtaining one or more final outputs from the set of trained machine learning models, and extracting, from the one or more final outputs, one or more predicted sentences from the text in the image. Each of the one or more predicted sentences includes a probable sequence of words.