Abstract: Systems and methods for data augmentation are provided. One aspect of the systems and methods include receiving an image that is misclassified by a classification network; computing an augmentation image based on the image using an augmentation network; and generating an augmented image by combining the image and the augmentation image, wherein the augmented image is correctly classified by the classification network.

Abstract: In implementations of systems for assistive digital form authoring, a computing device implements an authoring system to receive input data describing a search input associated with a digital form. The authoring system generates an input embedding vector that represents the search input in a latent space using a machine learning model trained on training data to generate embedding vectors in the latent space. A candidate embedding vector included in a group of candidate embedding vectors is identified based on a distance between the input embedding vector and the candidate embedding vector in the latent space. The authoring system generates an indication of a search output associated with the digital form for display in a user interface based on the candidate embedding vector.

Abstract: Techniques for document segmentation. In an example, a document processing application segments an electronic document image into strips. A first strip overlaps a second strip. The application generates a first mask indicating one or more elements and element types in the first strip by applying a predictive model network to image content in the first strip and a prior mask generated from image content of the first strip. The application generates a second mask indicating one or more elements and element types in the second strip by applying the predictive model network to image content in the second strip and the first mask. The application computes, from a combined mask derived from the first mask and the second mask, an output electronic document that identifies elements in the electronic document and the respective element types.

Abstract: Techniques for document segmentation. In an example, a document processing application segments an electronic document image into strips. A first strip overlaps a second strip. The application generates a first mask indicating one or more elements and element types in the first strip by applying a predictive model network to image content in the first strip and a prior mask generated from image content of the first strip. The application generates a second mask indicating one or more elements and element types in the second strip by applying the predictive model network to image content in the second strip and the first mask. The application computes, from a combined mask derived from the first mask and the second mask, an output electronic document that identifies elements in the electronic document and the respective element types.

Abstract: Techniques for document segmentation. In an example, a document processing application segments an electronic document image into strips. A first strip overlaps a second strip. The application generates a first mask indicating one or more elements and element types in the first strip by applying a predictive model network to image content in the first strip and a prior mask generated from image content of the first strip. The application generates a second mask indicating one or more elements and element types in the second strip by applying the predictive model network to image content in the second strip and the first mask. The application computes, from a combined mask derived from the first mask and the second mask, an output electronic document that identifies elements in the electronic document and the respective element types.

Abstract: A corpus of documents is processed using, for example, algorithms including deep learning and deep neural networks (“DNN”), to extract fragments across the corpus of documents. The extracted fragments can then be edited individually and referenced by a plurality of documents so that changes to the fragments are reflected universally across a corpus of documents efficiently. In one example case, a computer-implemented method is provided for extracting fragments in a digital document. The method includes indexing said document to generate a document element ID sequence; processing said document element ID sequence to generate at least one fragment candidate; processing said at least one fragment candidate to generate at least one respective fragment; and utilizing said at least one fragment to perform a reconstruction of said document.

Abstract: Portion-level digital rights management (DRM) in digital content is described. In one or more embodiments, a selection of a portion of the digital content is received at a computing device. Then, a policy is assigned to the selected portion by adding a markup element with an identifier to the selected portion. Based on the assigned policy, the selected portion is encrypted without encrypting another portion of the digital content. Subsequently, access to the selected portion is controlled based on the policy independently of the other portion. In this way, different portions of a single document can be protected with different policies. Different users may then have access to different portions of the digital content based on their user ID being associated with a particular policy, which improves security and management of distributable digital content.

Abstract: Digital form optimization techniques are disclosed which reduce the number of segments in empty digital forms that consumers of the empty digital forms need to complete. In some examples, a method may include determining potentially linkable segments in an empty digital form, determining a type of link to create for a potentially linkable segment of the potentially linkable segments, and providing a recommendation to create the determined type of link for the potentially linkable segment. The method may also include creating the determined type of link for the potentially linkable segment in response to a determination of an acceptance of the recommendation.

Abstract: Digital form optimization techniques are disclosed which reduce the number of segments in empty digital forms that consumers of the empty digital forms need to complete. In some examples, a method may include determining potentially linkable segments in an empty digital form, determining a type of link to create for a potentially linkable segment of the potentially linkable segments, and providing a recommendation to create the determined type of link for the potentially linkable segment. The method may also include creating the determined type of link for the potentially linkable segment in response to a determination of an acceptance of the recommendation.

Abstract: Techniques for processing of digital documents using, for example, algorithms including deep learning and deep neural networks (“DNN”), to extract fragments across a corpus of documents. The extracted fragments can then be edited individual and referenced by a plurality of documents so that changes to the fragments are reflected universally across a corpus of documents efficiently. In one example case, a computer-implemented method is provided for extracting fragments in a digital document. The method includes indexing said document to generate a document element ID sequence; processing said document element ID sequence to generate at least one fragment candidate; processing said at least one fragment candidate to generate at least one respective fragment; and utilizing said at least one fragment to perform a reconstruction of said document.

Abstract: Portion-level digital rights management (DRM) in digital content is described. In one or more embodiments, a selection of a portion of the digital content is received at a computing device. Then, a policy is assigned to the selected portion by adding a markup element with an identifier to the selected portion. Based on the assigned policy, the selected portion is encrypted without encrypting another portion of the digital content. Subsequently, access to the selected portion is controlled based on the policy independently of the other portion. In this way, different portions of a single document can be protected with different policies. Different users may then have access to different portions of the digital content based on their user ID being associated with a particular policy, which improves security and management of distributable digital content.