Abstract: Example embodiments of systems and methods for providing a video call between a first party and a second party. The method includes detecting an attempt to establish the video call by monitoring a voice call between the first party and the second party; authenticating the first and second parties; receiving from the first and second parties respective voice acceptances to invitations to establish the video call; retrieving video call identifications of the first and second parties; and establishing the video call without revealing the video call identification of the first party to the second party and the video call identification of the second party to the first party. A server uses credentials of a first party to request if that party would allow access of his identifying information to a second party and use that credential to further authenticate the first party.

Abstract: A method includes storing, by one or more processors of one or more computing devices, a plurality of datasets in a non-transitory computer memory associated with the one or more computing devices. A plurality of index representations is generated where each one of the plurality of index representations includes a compressed representation of a respective one of the plurality of datasets. The plurality of index representations is stored in the non-transitory computer memory. A sample dataset is received by the one or more processors. A sample dataset representation is generated that includes a compressed representation of the sample dataset. A determination that at least one of the plurality of datasets is most similar to the sample dataset based on the sample dataset representation and the plurality of index representations is performed.

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: A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.

Abstract: A computer-implemented method includes tracking, by a computing device, user browsing activity of a first page having known elements; mapping, by the computing device, the user browsing activity to the known elements; storing, by the computing device, mapping information that maps the user browsing activity to the known elements; tracking, by the computing device, user browsing activity of a second page having unknown elements; identifying, by the computing device, the unknown elements based on the mapping information and the user browsing activity of the second page; and executing, by the computing device, one or more computer-based instructions based on the determining the unknown elements that were identified.

Abstract: System and devices for live captioning events is disclosed. The system may receive event calendar data and a first plurality of caption files and preselect a first caption file based on the event calendar data. The system may then access an audiovisual recorder of a user device, and receive a first feedback from the recorder. The system may then determine whether the first caption file matches the first feedback. When there is a match, the system may determine a first synchronization between the caption file and the feedback. When there is no match, the system may determine if there is a match with a second caption file of the first plurality of caption files and determine a second synchronization. When the second caption file does not match, the system may receive at least a third caption file over a mobile network and determine a third synchronization for display.

Abstract: Apparatuses, systems and methods are described herein for separately collecting and storing form contents. Different information may be collected from a user on a form. Based on determining that portions of the form request a first type of information, an extended reality (XR) environment may be provided to the user. The user may provide the first type information via an input method in the XR environment. The user may provide a second type of information using a different input method outside of the XR environment. The first type of information may be processed and stored in a different database as compared to the second type of information. The database storing the first type of information may have a higher security standard than the database storing second type of information.

Abstract: A device detects a communication involving a user associated with an account and a service representative, and sends, to a user device associated with the account, an authentication notification that causes the user device to display an authentication field for the user. The device sends, to a service representative device associated with the service representative, a message that indicates that the service representative is to request, via the communication, the user to enter personal information associated with the user into the authentication field, where the user device is configured to generate a first authentication code based on a user input received from the user device in the authentication field. The device generates a second authentication code based on personal information associated with the account from a data structure, receives the first authentication code, and performs an action based on the first authentication code and the second authentication code.

Abstract: Randomizations of a web page may be generated in advance and provided to a client. The client may store the randomizations in its cache. Multiple randomizations for the same web page may be provided to the client and stored in the client's cache. When a request for a web page is made, it is determined if the client has any cached randomizations. Randomizations for the probable next web page to be requested by the client may be provided to the client for storage in the cache. For example, the probability that a link will be clicked or a website visited may be determined. Those web pages and websites with higher probabilities may be determined. Randomizations for those web pages are then provided to the client for use.

Abstract: Disclosed herein are system, method, and apparatus for generating labels for k-means clusters. The method includes accessing a plurality of data records from a database repository, and storing the plurality of data records into at least one of primary or secondary memory associated with at least one computer processor performing the method, along with a cluster number for each data record. All data records having a same cluster number form a cluster, and each record has been categorized or designated a cluster number out of a total K number of clusters. The method includes for each of a plurality of classification features, performing cluster-based analysis for a first cluster with respect to a single feature to generate a single feature overlap score. The method includes sorting, grouping, and generating a naming label for the first cluster based on the predetermined number of features having the lowest overlap scores.

Abstract: Systems as described herein may label data to preserve privacy. An annotation server may receive a document comprising a collection of text representing a plurality of confidential data from a first computing device. The annotation server may convert the document to a plurality of text embeddings. The annotation server may input the text embeddings into a machine learning model to generate a plurality of synthetic images, and receive a label for each of the plurality of synthetic images from a third-party labeler. Accordingly, the annotation server may send the confidential data and the corresponding labels to a second computing device.

Abstract: Various embodiments are directed to a system that utilizes regular expression (regex) to recognize at least portions of characters, words, text, numbers, etc. in a structured or unstructured dataset, any patterns associated therewith, and/or similarities between the determined patterns. In examples, a regex-based pattern recognition platform may receive a dataset and determine whether at least a first regex pattern and a second regex pattern can be identified. The occurrences of the first and second regex patterns and the frequency of those occurrences may reveal something about the dataset itself or any patterns contained therein.

Abstract: Systems and methods for providing encryption and decryption involving texture warping, comprising: obtaining a visual input; obtaining a private key; generating an encrypted visual representation (visual representation A) based on the private key and the visual input; determining at least one 3D object configured so that the private key is derivable when the visual representation A is mapped to a digital model of the at least one 3D object; transmitting the visual representation A to a second computing device associated with a second user; transmitting a representation of the digital model of the at least one 3D model to the second computing device; and instructing the second computing device so that the second computing device is configured to map the visual representation A to the digital model generated based on the representation of the digital model of the at least one 3D model to extract the private key.

Abstract: Disclosed are examples for providing functions to receive a media file to be stored in a media repository. In the examples, a location in the media repository may be assigned to the media file. A media file address in a blockchain platform may be assigned to the media file. Metadata including the assigned location in the media repository and the assigned media file address in the blockchain platform may be added to the media file. A media file hash value may be generated by applying a hash function to the media file including the metadata. The media file hash value may be included in a message and uploaded to the assigned media file address in the blockchain platform as a transaction in the blockchain. An indication that the media file is uploaded to the media repository may be delivered to a subscriber device from which the media file was received.

Abstract: Systems and methods for distorting CAPTCHA images with generative adversarial networks include an image distortion interface that can select an image record from a database, determine the size of the selected image, and apply an adversarial attack algorithm to create an array of pixels that is the same size as the selected image so that the majority of the pixels in the array are zero values and the remaining pixels in the array are in the red-green-blue value range. The image distortion interface can merge the array of pixels with the selected image to form a distorted image. A server can include a CAPTCHA test interface that can select a set of images having the same label, retrieve corresponding distorted images, and provide a CAPTCHA test using the distorted images. The CAPTCHA test can use distorted images with different applied adversarial attack algorithms.

Abstract: An exemplary system, method, and computer-accessible medium can include, for example, receiving an original dataset(s), receiving a synthetic dataset(s), training a model(s) using the original dataset(s) and the synthetic dataset(s), and evaluating the synthetic dataset(s) based on the training of the model(s). The model(s) can include a first model and a second model, and the first model can be trained using the original dataset(s) and the second model can be trained using the synthetic dataset(s). The synthetic dataset(s) can be evaluated by comparing first results from the training of the first model to second results from the training of the second model.

Abstract: Disclosed are examples for adjusting screen brightness based on screen content being presented on a display screen of a mobile device. The described examples may determine a time at which the screen content is to be evaluated. The screen content is categorized based on the evaluation. A category of the screen content may be input into a machine learning algorithm that may be used to determine whether a screen brightness adjustment is appropriate. If a screen brightness adjustment is appropriate, a degree of the screen brightness adjustment may be determined.

Abstract: Various embodiments for a system to utilize user's location pattern as an authentication parameter are disclosed. An embodiment operates by retrieving a location history of a user based on past locations of a user equipment (UE) device at various times and traffic data associated with the location history. A request to access a protected application is received and a present location of the UE device at a time associated with the request is determined. A locational pattern is generated based on both the location history of the user and the traffic data. The present location of the UE device is compared with the locational pattern, and it is determined that a level of authentication necessary to grant access to the protected application is satisfied based on both the comparing and a determination that the present location falls within the locational range generated based on the traffic data.

Abstract: Example embodiments of systems and methods for providing a video call between a first party and a second party. The method includes detecting an attempt to establish the video call by monitoring a voice call between the first party and the second party; authenticating the first and second parties; receiving from the first and second parties respective voice acceptances to invitations to establish the video call; retrieving video call identifications of the first and second parties; and establishing the video call without revealing the video call identification of the first party to the second party and the video call identification of the second party to the first party.

Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.