Abstract:
A method is provided for organizing data sets. In use, an automatic decision system is created or updated for determining whether data elements fit a predefined organization or not, where the decision system is based on a set of preorganized data elements. A plurality of data elements is organized using the decision system. At least one organized data element is selected for output to a user based on a score or confidence from the decision system for the at least one organized data element. Additionally, at least a portion of the at least one organized data element is output to the user. A response is received from the user comprising at least one of a confirmation, modification, and a negation of the organization of the at least: one organized data element. The automatic decision system is recreated or updated based on the user response. Other embodiments are also presented.
Abstract:
According to one aspect, a computer-implemented method of discovering processes for robotic process automation (RPA) includes: recording a plurality of event streams, each event stream corresponding to a human user interacting with a computing device to perform one or more tasks; concatenating the event streams; segmenting some or all of the concatenated event streams to generate one or more application traces performed by the user interacting with the computing device, each application trace corresponding to one of the one or more tasks performed by the user; clustering the traces according to a task type; identifying, from among some or all of the clustered traces, one or more candidate processes for robotic automation; prioritizing the candidate processes; and selecting at least one of the prioritized candidate processes for robotic automation. Corresponding systems and computer program products are also described.
Abstract:
Systems, computer program products, and techniques for detecting and/or reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be detected and/or reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, reconstructing an object depicted in a digital image includes using a processor to: detect a plurality of identifying features of the object, where the identifying features are located internally with respect to the object; and reconstruct the digital image of the object within a three dimensional coordinate space based at least in part on some or all of the identifying features.
Abstract:
An efficient method and system to enhance digital acquisition devices for analog data is presented. The enhancements offered by the method and system are available to the user in local as well as in remote deployments yielding efficiency gains for a large variety of business processes. The quality enhancements of the acquired digital data are achieved efficiently by employing virtual reacquisition. The method of virtual reacquisition renders unnecessary the physical reacquisition of the analog data in case the digital data obtained by the acquisition device are of insufficient quality. The method and system allows multiple users to access the same acquisition device for analog data. In some embodiments, one or more users can virtually reacquire data provided by multiple analog or digital sources. The acquired raw data can be processed by each user according to his personal preferences and/or requirements. The preferred processing settings and attributes are determined interactively in real time as well as non real time, automatically and a combination thereof.
Abstract:
According to one embodiment, a computer-implemented method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting an identifier of the document from the image based at least in part on the OCR; comparing the identifier with content from one or more reference data sources, wherein the content from the one or more reference data sources comprises global address information; and determining whether the identifier is valid based at least in part on the comparison. The method may optionally include normalizing the extracted identifier, retrieving additional geographic information, correcting OCR errors, etc. based on comparing extracted information with reference content. Corresponding systems and computer program products are also disclosed.
Abstract:
Systems and methods for mobile image data capture and processing are disclosed. The techniques encompass receipt or capture of digital image data, detecting an object such as a document depicted in a digital image corresponding to the digital image data, processing the digital image to improve image quality, classifying the object from the processed image data, and extracting useful information from the object. Processing may improve image quality by correcting artifacts such as distortion, skew, blur, shadows, etc. common to digital images captured using mobile devices. Classification is based on identifying unique features (and/or combinations thereof) within the image data and determining whether the identified features indicate the object belongs to a class of known objects having similar characteristics, or is unique to all known classes. Extraction is based in whole or in part on object classification. All operations may be performed using mobile technology exclusively.
Abstract:
According to one embodiment, a computer-implemented method for confirming/rejecting a most relevant example includes: generating a binary decision model by training a binary classifier using a plurality of training documents; classifying one or more test documents into one of a plurality of categories using the binary decision model, wherein the one or more test documents lack a user-defined category label; selecting a most relevant example of the classified test documents from among the classified test documents; displaying, using a display of the computer, the most relevant example of the classified test documents to a user; receiving, via the computer and from the user, a confirmation or a negation of a classification label of the most relevant example of the classified test documents; and storing the confirmation or the negation of the classification label of the most relevant example of the classified test documents to a memory of the computer.
Abstract:
The presently disclosed inventive concepts encompass capturing video data using a mobile device, streaming the captured video data to a server for processing of the video data in real-time or near-real time, and providing the server's processing result to the mobile device for additional analysis and/or processing of the captured video data, the processing result, or both. In one embodiment an image processing server is configured to: process, in real time, input streamed to the server from a mobile device, the input comprising one or more frames of digital video data; and output a result of processing the input to the mobile device. In another embodiment, a method includes capturing video data using a mobile device, streaming the video data to an image processing server, receiving a processing result from the server, and further processing the captured video data and/or the processing result using the mobile device.
Abstract:
Systems, computer program products, and techniques for reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, a computer-implemented method of reconstructing an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; and reconstructing the digital image of the object within a three dimensional coordinate space based at least in part on some or all of the plurality of identifying features.
Abstract:
In one embodiment, a method includes performing optical character recognition (OCR) on an image of a financial document and at least one of: (a) correct OCR errors in the financial document using at least one of textual information from a complementary document and predefined business rules; (b) normalize data from the complementary document using at least one of textual information from the financial document and the predefined business rules; and (c) normalize data from the financial document using at least one of textual information from the complementary document and the predefined business rules. Exemplary systems and computer program products are also disclosed.