Abstract: In certain aspects, the disclosed implementations include methods and systems for dynamically generating and determining transaction affinity relationship information associated with a set of merchants involved in a set of transactions. In certain implementations, the transaction affinity relationship information may reflect affinity relationships between merchant chains in a merchant affinity network. The disclosed implementations may receive an adjustment to an affinity relationship associated with a merchant chain, and based on the adjustment, predicts one or more changes to affinity relationships associated with other merchant chains in the merchant affinity network.

Abstract: In certain aspects, the disclosed implementations include methods and systems for dynamically generating and providing transaction affinity recommendation data. In certain implementations, the transaction affinity recommendation data may include information that identifies a target merchant and associated merchant promotion data that may be generated based on a dynamic analysis of transaction data corresponding to an account record. The disclosed implementations may determine temporal relationships between pairs of sequential transactions corresponding to the account record, and based on such relationships, may identify pairs of transactions involving separate merchants. The disclosed implementations may determine affinity relationships associated with one or more pairs of the temporally related transactions and a target merchant, and based on such relationships, generate and provide the transaction affinity recommendation data.

Abstract: In certain aspects, the disclosed implementations include methods and systems for dynamically generating and providing transaction affinity recommendation data. In certain implementations, the transaction affinity recommendation data may include information that identifies a target merchant and associated merchant promotion data that may be generated based on a dynamic analysis of transaction data corresponding to an account record. In some aspects, the disclosed implementations may perform processes that determine adjustments to the merchant recommendation data based on one or more parameters associated with potential next merchants included in the merchant recommendation data. The disclosed implementations may analyze weigh values assigned to the one or more parameters, and based on the weight values and parameter information, may determine a different merchant is to be recommended.

Abstract: An example process described herein may involve capturing an image including a document; identifying a first part of the document, wherein the first part of the document is identified based on detecting an outline of the first part of the document; analyzing a first region of the image determined in relation to the first part of the document to detect a second part of the document based on an outline of the second part of the document; identifying the second part of the document based on detecting the first part of the document and analyzing the first region; combining the first part of the document with the second part of the document to generate object data associated with the document, wherein the object data includes data representative of a gap between the first part of the document and the second part of the document; and performing an action related to the object data.

Abstract: A user device detects, in a field of view of the camera, a first side of a document, and determines first information associated with the first side of the document. The user device selects a first image resolution based on the first information and captures, by the camera, a first image of the first side of the document according to the first image resolution. The user device detects, in the field of view of the camera, a second side of the document, and determines second information associated with the second side of the document. The user device selects a second image resolution based on the second information, and captures, by the camera, a second image of the second side of the document according to the second image resolution. The user device performs an action related to the first image and the second image.

Abstract: A user device may capture an image including an object, and may identify the object, including determining an outline of the object. The user device may determine a first center point of the object and an angle of orientation of the object in relation to the image. The user device may rotate the image based on the angle of orientation, including changing one or more dimensions of the image. The user device may, after rotating the image, determine the one or more dimensions of the rotated image, calculate one or more offset values associated with changing the one or more dimensions of the rotated image, and determine a second center point of the object based on the first center point and the one or more offset values. The user device may perform an action related to the rotated image based on determining the second center point of the object.

Abstract: An example process described herein may involve capturing an image including a document; identifying a first part of the document, wherein the first part of the document is identified based on detecting an outline of the first part of the document; analyzing a first region of the image determined in relation to the first part of the document to detect a second part of the document based on an outline of the second part of the document; identifying the second part of the document based on detecting the first part of the document and analyzing the first region; combining the first part of the document with the second part of the document to generate object data associated with the document, wherein the object data includes data representative of a gap between the first part of the document and the second part of the document; and performing an action related to the object data.

Abstract: A system including a processor; and a memory having stored thereon computer program code that, when executed by the processor, controls the processor to: receive data indicative of a plurality of sequence diagrams; for each of the plurality of sequence diagrams, generate a corresponding architecture diagram by: identifying a plurality of participants within the sequence diagram, transforming each of the plurality of participants into a plurality of nodes, identifying a plurality of messages identifying at least one message participant, and transforming the identified plurality of messages by establishing a single edge between respective nodes of the plurality of nodes corresponding to message participants identified by one or more messages of the plurality of messages; and merge the corresponding architecture diagrams of each of the plurality of sequence diagrams to generate a master architecture diagram.

Abstract: In some implementations, a device may detect edges in an image, and may identify, based on the edges, a rectangle that bounds a document in the image. The device may detect lines in the image, and may identify edge candidate lines by discarding one or more of the lines. The device may identify intersection points where lines, included in the edge candidate lines, intersect with one another. The device may identify corner candidate points by discarding one or more points included in the intersection points, and may identify a corner point included in the corner candidate points. The corner point may be a point, included in the corner candidate points, that is closest to one corner of the bounding rectangle. The device may perform perspective correction on the image of the document based on identifying the corner point.

Abstract: A device may capture a plurality of preview frames of a document, and for each preview frame of the plurality of preview frames, process the preview frame to identify an object in the preview frame. Processing the preview frame may include converting the preview frame into a grayscale image, generating a blurred image based on the grayscale image, detecting a plurality of edges in the blurred image, defining at least one bounding rectangle based on the plurality of edges, and determining an outline of the object based on the at least one bounding rectangle. The device may determine whether a value of an image parameter, associated with the one or more preview frames, satisfies a threshold, and provide feedback to a user of the device, or automatically capture an image of the document, based on determining whether the value of the image parameter satisfies the threshold.