Abstract: A system includes a customer authentication system and an automatic teller machine (ATM). The ATM includes a display, one or more memory devices storing software instructions, and one or more processors configured to: execute the software instructions to perform operations to display an item on display; store information regarding the item; receive from a customer device captured information regarding the item; receive from the customer device identifying information of a customer; send the identifying information to the customer authentication system; compare the captured information with the information stored in the one or more memory devices; authenticate the customer device based on the comparison; and allow access to the customer account via the ATM after the authentication.

Abstract: In some implementations, a system may receive interaction data based on an interaction of a user with a terminal, wherein the interaction data indicates a location of the terminal. The system may determine a plurality of entities having a corresponding plurality of locations that are within a geographic area that includes the location of the terminal. The system may determine, based on the plurality of entities, one or more categories for categorizing a purpose associated with the interaction of the user with the terminal. The system may transmit, to a user device of the user, information that identifies the one or more categories. The system may receive, from the user device, information that identifies one or more user-specified categories of the one or more categories. The system may store, in the database, a record that includes the information that identifies the one or more user-specified categories.

Abstract: In some implementations, a system may receive a shell script associated with a computing device. The system may generate a character frequency feature vector based on the shell script. The system may input text of the shell script to a convolutional neural network (CNN) branch of a trained deep learning model. The system may input the character frequency feature vector to a feedforward neural network (FNN) branch of the trained deep learning model. The system may determine using the trained deep learning model, a respective probability score for each of a plurality of obfuscation types for the shell script based on a combined output of the CNN branch and the FNN branch. The system may detect whether the shell script is obfuscated based on the respective probability score for each of the plurality of obfuscation types determined for the shell script.

Abstract: Techniques and apparatus for an interactive element presentation process are described. In one embodiment, for example, an apparatus may include logic operative to store a plurality of model specifications for computational models, monitor the object storage service for at least one model event using a first serverless computing service, provide the plurality of model specifications associated with the at least one model event to one of a plurality of serverless computing clusters, generate model data for each of the plurality of model specifications, store the model data for each of the plurality of computational models in the object storage service, monitor the object storage service for at least one data event associated with the model data using a second serverless computing service, cause the plurality of instances to generate a plurality of trained model specifications based on training of the plurality of computational models. Other embodiments are described.

Abstract: A computer-implemented method for template generation may include: receiving a first plurality of variables, each of the first plurality of variables specifying a feature to be implemented in a new template for document generation; for each of a plurality of existing templates for document generation, determining a degree of similarity between the first plurality of variables and a plurality of variables included in the respective existing template; upon determining that none of the degrees of similarity respectively determined for the plurality of existing templates satisfies a similarity threshold, determining that a combination of variables from two or more of the plurality of existing templates has a degree of similarity with the first plurality of variables satisfying the similarity threshold; and generating the new template based on the two or more of the plurality of existing templates.

Abstract: Transaction cards, systems and methods involving an on-card display and an associated mobile computing device utilized for authenticating transactions are disclosed. In one embodiment, an exemplary transaction card may comprise transaction circuitry configured to conduct purchase transactions involving a mobile computing device coupled to or associated with the transaction card, communication circuitry configured to communicate with a provider of the transaction card, an e-ink display configured to display a QR code on the transaction card for use in authentication, data storage configured to store the QR code, and computer readable media having instructions for initiating a second-factor authentication process and displaying the QR code on the e-ink display to be captured by the mobile computing device and transmitted to a system or server for validating the second-factor authentication process.

Abstract: Disclosed embodiments may include a system for measuring document legibility. The system may automatically receive document image data from a user device. The system may then process the image data using optical character recognition to create language data containing a plurality of words. The system may then obtain an overall number by counting the plurality of words in the language data. The system may then identify and count the common words within the plurality of words by comparing the plurality of words to words in a database. A score may be obtained by dividing the common word number by the overall number. The score may then be compared to a legibility threshold. If the score is below the threshold, the system may determine the document is illegible. If the score is above the threshold, the system may determine the document is legible.

Abstract: The present disclosure relates to systems and methods for backing up a distributed database provided as a database instance across servers within a first geographic region. In one example, such a system may include at least one processor configured to: generate and transmit a command to duplicate the distributed database in object databases on first region servers; generate and transmit a command to duplicate the object databases on servers in at least a second geographic region independent from servers in the first region; and, when an error is detected with at least one server within the first region: generate and transmit a command to initiate a new distributed database on second region servers, generate and transmit a command to populate the new distributed database using the object databases on second region servers, and generate and transmit a command to re-route traffic from the distributed database to the new distributed database.

Abstract: A capacitive sensor includes a first conductive structure; a second conductive structure that is counter to the first conductive structure, wherein the second conductive structure is movable relative to the first conductive structure in response to an external force acting thereon, wherein the second conductive structure is capacitively coupled to the first conductive structure to form a first capacitor having a first capacitance that changes with a change in a distance between the first conductive structure and second conductive structure; a signal generator configured to apply a first electrical signal step at an input or at an output of the first capacitor to induce a first voltage transient response at the output of first capacitor; and a diagnostic circuit configured to detect a fault in the capacitive sensor by measuring a first time constant of the first voltage transient response and detecting the fault based on the first time constant.

Abstract: Techniques to improve detection and security of images, including formation and detection of matrix-based images. A histogram may be used to determine a most prevalent plurality of colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors. A matrix barcode may be generated based on the related plurality of colors.

Abstract: A non-transitory computer-readable medium stores instructions causing a processor to generate a menu displaying representations of a plurality of cards, the cards having associated card data; receive, from a user input device, a selection corresponding to a selected one of the cards; update the menu to display a representation of the selection; and authorize transmission of the card data associated with the selected card to complete a transaction.

Abstract: Systems and methods for processing image data representing a document to remove deformations contained in the document are disclosed. A system may include one or more memory devices storing instructions and one or more processors configured to execute the instructions. The instructions may instruct the system to provide, to a machine learning system, a training dataset representing a plurality of documents containing a plurality of training deformations. The instructions may also instruct the system to use the machine learning system to process image data representing a target document containing a target document deformation. The machine learning system may generate restored image data representing the target document with the target document deformation removed. The instructions may further instruct the system to provide the restored image data to at least one of a graphical user interface, an image storage device, or a computer vision system.

Abstract: Methods and systems are described herein for leveraging artificial intelligence to sanitize sensitive data and prevent the data from leaving the mobile device and/or be exposed to unauthorized third parties. More specifically, methods and systems are described for a novel and unconventional architecture for a data sanitization application, a novel and unconventional delivery format for the data sanitization model, and a novel and unconventional output format of the data sanitization model.

Abstract: Methods and systems are described herein for authorizing limited user access to resources of other users using NFTs. A resource access system may be used to authorize access. The system may receive a first request for performing an action using a resource associated with a first user, and in response to the first request, obtain an encrypted payload from a blockchain node of a blockchain. The system may transmit a command to the second device to decrypt the encrypted payload using the second cryptography-based storage application and receive the access token and the one or more access parameters from the second device. In response to determining that metadata of the first request matches the one or more access parameters of the access token, the system may transmit a request to perform the action.

Abstract: Methods and systems for uses and/or improvements to blockchain technology. In particular, the methods and systems described herein implement a novel cryptographic resource standard that provides functionality for complex communications. The novel cryptographic resource standard allows for blockchain functions that may involve single cryptographic resource transfers or batch cryptographic resource transfers as well as on-chain batching of one or more cryptographic resources.

Abstract: Systems and methods for transforming data for a batch-based legacy software program into data suitable for processing by a streaming-based new software program. In some aspects, the system generates an information stream for multiple threads from batch information received from the legacy software program. The system processes the information stream for the multiple threads using the new software program. If there is a mismatch between outputs of the legacy and new software programs for at least one thread, the system adjusts a data model of the new software program to address the mismatch and generates an updated information stream for processing by the new software program.

Abstract: In some aspects, a computing system may aggregating multiple counterfactual samples so that machine learning explanations can be generated for sub-populations. In addition, methods and systems described herein use machine learning and counterfactual samples to determine text to use in an explanation for a model's prediction. A computing system may also train machine learning models to not only determine whether a request to perform an action should be accepted, but also to generate output that is consistent with output generated by previous machine learning models. Further, a computing system may generate counterfactual samples based on user preferences. A computing system may obtain preferences and then apply a penalty or adjustment parameter such that when a counterfactual sample is created, the computing system is forced to change one or more features indicated by the preferences to create the counterfactual sample.

Abstract: In some aspects, a computing system may aggregating multiple counterfactual samples so that machine learning explanations can be generated for sub-populations. In addition, methods and systems described herein use machine learning and counterfactual samples to determine text to use in an explanation for a model's prediction. A computing system may also train machine learning models to not only determine whether a request to perform an action should be accepted, but also to generate output that is consistent with output generated by previous machine learning models. Further, a computing system may generate counterfactual samples based on user preferences. A computing system may obtain preferences and then apply a penalty or adjustment parameter such that when a counterfactual sample is created, the computing system is forced to change one or more features indicated by the preferences to create the counterfactual sample.

Abstract: Embodiments disclosed are directed to a system that performs steps to perform enhanced device fingerprinting. The system at least at receives from an application, a plurality of device attributes identifying a client device on which the application is being used. The plurality of device attributes includes a push token provided by a push token service to the client device. The push token is uniquely paired to the client device. The system further transmits, to a device database, the plurality of device attributes for storage in a device profile. The system also transmits, to the application, a push notification based on the push token. The system receives, from the application, a deliverable status indicating whether the push notification was successfully transmitted to the client device, and transmits, to a notification database, the deliverable status for storage in a notification delivery profile. The system can use the information to authenticate a device.

Abstract: Systems and methods for predicting differentiating features from tabular data for two different populations. In some aspects, the systems and methods provide for receiving first data entries and second data entries and generating a first graph based on a data entry from the first data entries and a second graph based on a data entry from the second data entries. A first node in the first graph is determined to correspond to a second node in the second graph. A first set of graph embeddings is generated based on the first graph. A second set of graph embeddings is generated based on the second graph. Using a machine learning model, the first set of graph embeddings and the second set of graph embeddings are processed to identify at least one feature indicative of a difference between the first data entries and the second data entries.