Abstract: In some implementations, a monitoring system may capture a set of screenshots that depict behavior associated with a bot during an automation run. The monitoring system may obtain one or more logs that include information describing the behavior of the bot during the automation run. The monitoring system may create, based on a portion of the set of screenshots, video data that includes a sequence of frames related to an anomaly or a failure event that occurred during the automation run. The monitoring system may annotate, based on the information included in the one or more logs, the sequence of frames with metadata describing the behavior of the bot. The monitoring system may provide, to a user device, user interface data that includes the video data and the metadata used to annotate the sequence of frames.

Abstract: Disclosed are methods and systems for generating a virtual tag for an item in a physical environment. For instance, an image of the physical environment captured by and displayed on a user interface of a computing device may be provided as input to a trained machine learning model configured to identify the item including a first subset of item attributes. The item may be identified and information associated with the item, including a second subset of item attributes, may be received from a data store using the first subset. A spatial location of the item may be identified in the image. An icon may be generated for the item and rendered by the computing device for display on the user interface in association with the spatial location of the item in the image. The icon may be indicative of at least one item attribute from the first or second subset.

Abstract: In some implementations, an authentication system may receive, from a client device, a credential associated with a user account and a request to access a resource. The authentication system may transmit, to the client device, a request for an image of a customized physical security token associated with the user account. The authentication system may receive, from the client device, a first image. The authentication system may compare the first image with a representation of a second image of the customized physical security token associated with the user account. The authentication system may grant or denying access to the resource based on comparing the first image with the representation of the second image.

Abstract: A monitoring platform may obtain information that identifies a product or service and may collect one or more reviews associated with the product or service from a plurality of sources, wherein each review includes respective review information. The monitoring platform may process the one or more reviews to determine respective additional review information associated with each review of the one or more reviews. The monitoring platform may select, using a machine learning model, a particular review, of the one or more reviews, based on the review information and the additional review information associated with the one or more reviews. The monitoring platform may cause display, on a display of a client device, of a prompt for a response to the particular review and may obtain the response from the client device. The monitoring platform may cause the response to be posted to a source associated with the particular review.

Abstract: Disclosed embodiments may include a system for managing assets. The system may establish a connection with a drone comprising Light Detection and Ranging (LiDAR) sensors and an image capture device. The system may receive, via the drone, image data via the LiDAR sensors and the image capture device. The system may identify, from the image data via computer vision, one or more assets, a condition of the one or more assets, and a location associated with the one or more assets. The system may generate a dynamic report comprising the one or more assets, the condition of the one or more assets, and the location associated with the one or more assets.

Abstract: A monitoring platform may obtain information that identifies a product or service and may collect one or more reviews associated with the product or service from a plurality of sources, wherein each review includes respective review information. The monitoring platform may process the one or more reviews to determine respective additional review information associated with each review of the one or more reviews. The monitoring platform may select, using a machine learning model, a particular review, of the one or more reviews, based on the review information and the additional review information associated with the one or more reviews. The monitoring platform may cause display, on a display of a client device, of a prompt for a response to the particular review and may obtain the response from the client device. The monitoring platform may cause the response to be posted to a source associated with the particular review.

Abstract: Disclosed embodiments include systems, devices, and methods for extending a view of an interface by way of augmented reality glasses. Web page content can be identified for presentation outside the purview of a web browser. The content can be saved to a network-accessible store. Subsequently, a request is sent, including the location of the network-accessible store, to augmented reality glasses. The content can be acquired from the location by the augmented reality glasses. Subsequently, the content can be rendered by the augmented reality glasses in a manner that extends the view beyond the web browser and physical display.

Abstract: Disclosed embodiments include systems, devices, and methods for extending a view of an interface by way of augmented reality glasses. Web page content can be identified for presentation outside the purview of a web browser. The content can be saved to a network-accessible store. Subsequently, a request is sent, including the location of the network-accessible store, to augmented reality glasses. The content can be acquired from the location by the augmented reality glasses. Subsequently, the content can be rendered by the augmented reality glasses in a manner that extends the view beyond the web browser and physical display.

Abstract: In some implementations, an authentication system may receive, from a client device, a credential associated with a user account and a request to access a resource. The authentication system may transmit, to the client device, a request for an image of a customized physical security token associated with the user account. The authentication system may receive, from the client device, a first image. The authentication system may compare the first image with a representation of a second image of the customized physical security token associated with the user account. The authentication system may grant or denying access to the resource based on comparing the first image with the representation of the second image.

Abstract: In some implementations, an authentication system may receive, from a client device, a credential associated with a user account and a request to access a resource. The authentication system may transmit, to the client device, a request for an image of a customized physical security token associated with the user account. The authentication system may receive, from the client device, a first image. The authentication system may compare the first image with a representation of a second image of the customized physical security token associated with the user account. The authentication system may grant or denying access to the resource based on comparing the first image with the representation of the second image.

Abstract: A method for color correction of an image includes generating a plurality of gain modules for an image scanning device, where each gain module of the plurality of gain modules includes a ratio of a maximum light intensity and a scanned white intensity. The method may further include generating a plurality of color correction modules, wherein each color correction module is associated with a respective gain module. Responsive to receipt of instructions to perform a scan of a document, the method may include identifying a color correction module of the plurality of color correction modules to apply and applying the identified color correction module to an image of the scanned document.

Abstract: A monitoring platform may obtain information that identifies a product or service and may collect one or more reviews associated with the product or service from a plurality of sources, wherein each review includes respective review information. The monitoring platform may process the one or more reviews to determine respective additional review information associated with each review of the one or more reviews. The monitoring platform may select, using a machine learning model, a particular review, of the one or more reviews, based on the review information and the additional review information associated with the one or more reviews. The monitoring platform may cause display, on a display of a client device, of a prompt for a response to the particular review and may obtain the response from the client device. The monitoring platform may cause the response to be posted to a source associated with the particular review.

Abstract: In some implementations, an authentication system may receive, from a client device, a credential associated with a user account and a request to access a resource. The authentication system may transmit, to the client device, a request for an image of a customized physical security token associated with the user account. The authentication system may receive, from the client device, a first image. The authentication system may compare the first image with a representation of a second image of the customized physical security token associated with the user account. The authentication system may grant or denying access to the resource based on comparing the first image with the representation of the second image.

Abstract: A monitoring platform may obtain information that identifies a product or service and may collect one or more reviews associated with the product or service from a plurality of sources, wherein each review includes respective review information. The monitoring platform may process the one or more reviews to determine respective additional review information associated with each review of the one or more reviews. The monitoring platform may select, using a machine learning model, a particular review, of the one or more reviews, based on the review information and the additional review information associated with the one or more reviews. The monitoring platform may cause display, on a display of a client device, of a prompt for a response to the particular review and may obtain the response from the client device. The monitoring platform may cause the response to be posted to a source associated with the particular review.

Abstract: A computer-implemented method for assessing automation may include receiving risk factor data from a user. The risk factor data may correspond to one or more risk factors, as applied to an automation opportunity, wherein each risk factor has an associated risk inquiry and a factor weight. A risk score may be generated for each of the one or more risk factors, based on the risk factor data and a scoring matrix. A risk grade for the automation opportunity may be calculated based on the risk score for each of the one or more risk factors. Performance data related to the automation opportunity may be recorded and may be compared to the risk grade. Based on the comparison of the performance data to the risk grade, one or more risk factors, one or more factor weights, a scoring matrix, or a combination thereof, may be adjusted.

Abstract: A monitoring platform may obtain information that identifies a product or service and may collect one or more reviews associated with the product or service from a plurality of sources, wherein each review includes respective review information. The monitoring platform may process the one or more reviews to determine respective additional review information associated with each review of the one or more reviews. The monitoring platform may select, using a machine learning model, a particular review, of the one or more reviews, based on the review information and the additional review information associated with the one or more reviews. The monitoring platform may cause display, on a display of a client device, of a prompt for a response to the particular review and may obtain the response from the client device. The monitoring platform may cause the response to be posted to a source associated with the particular review.

Abstract: Examples herein involve retrieving a color transformation from a highlighter color transform, and processing an image using the color transformation to enhance highlighter colors in the image, the image scanned by a scanner using strobed illumination.

Abstract: Examples herein involve retrieving a color transformation from a highlighter color transform, and processing an image using the color transformation to enhance highlighter colors in the image, the image scanned by a scanner using strobed illumination.

Abstract: A scanner is disclosed. The scanner has three lights with three different colors. The scanner uses only two of the three lights when capturing each scan line. The scanner does this by alternating the use of two of the three colors every other scan line.

Abstract: A scanner is disclosed. The scanner captures three exposures for each color scan line. The scanner has a first, second and third light source that each produces a different color of light. The scanner uses the first and second light source for the first exposure. The scanner uses the first and third source for the second exposure. The scanner uses the second and third light source for the third exposure.