Multi-modal ensemble deep learning for start page classification of document image file including multiple different documents

A non-transitory computer-readable medium having executable instructions stored thereon that, when executed by a processor, cause the processor to perform operations comprising:

• obtaining a document image file including multiple pages corresponding to multiple documents;
• obtaining, for each page of the multiple pages, using multiple dependent models of a neural network, multiple feature embeddings, each of the feature embeddings corresponding to at least features of the page that are indicative of whether or not the page is a first page of one of the documents;
• combining, for each page of the multiple pages, the feature embeddings into combined feature embeddings;
• and
• generating, for each page of the multiple pages, based on the combined feature embeddings, using a neural network, a prediction output indicating whether or not the page is the first page of one of the documents,
• wherein the multiple feature embeddings of each comprise two or more feature embeddings selected from the group consisting of:
• first image features of a multi-page image including a combination of the page and an adjacent page;
• second image features of the page;
• textual features of the page;
• font features of the page and the adjacent page;
• and
• margin features of the page and the adjacent page,
• wherein a first feature embedding of the multiple feature embeddings comprises the first image features, and
• wherein the operations further comprise obtaining the first image features of each page by concatenating the page with the adjacent page to form the multi-page image.

A non-transitory computer-readable medium having executable instructions stored thereon that, when executed by a processor, cause the processor to perform operations comprising:

• obtaining a document image file including multiple pages corresponding to multiple documents;
• obtaining first multiple page images corresponding to the multiple pages;
• adding a blank page image to the first multiple page images to obtain second multiple page images;
• obtaining multiple multi-page images by combining every two consecutive page images of the second multiple page images into a multi-page image associated with a page of the multiple pages;
• and
• generating, for each page of the multiple pages, based at least on the multi-page image associated with the page, using a trained image classification model, a first prediction indicating whether or not the page is a first page of one of the documents.