Capital One Services, LLC

Thomas Oliver Cantrell

Joseph Ford, Iii

Methods and systems are described herein for identifying the location and nature of any blur within one or more images received as a user communication and generating an appropriate correction. The system utilizes a first machine learning model, which is trained to identify blurred components of inputted images and determine whether the blurred components are located in portions of the inputted images comprising textual information. The system may apply a corrective action selected by the first machine learning model, which may comprise stitching blurred images together to a sharp product image and/or some other method appropriate for rectifying images received.

Systems and methods for identifying and correcting blurred components within images

A computer implemented method, system, and non-transitory computer-readable device that may be used in a remote deposit environment. A plurality of differing neural networks, such as customizable neural networks, are selected, based on an architecture and features of the data field, to extract data from specific data fields on a document. The selected customizable neural networks are trained by historical or synthetic data corresponding to the data fields. Upon receiving, from a neural network Optical Character Recognition (OCR) system, a selected first trained customizable neural network model and at least a second selected trained customizable neural network model, the data fields are extracted, based on a series or parallel configuration of the customizable neural networks, and the extracted data communicated to a remote deposit process.

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Maidens, VA, United States of America

Thomas Oliver Cantrell