A method for performing automatic visual inspection includes: capturing visual information of an object using a scanning system including a plurality of cameras; extracting, by a computing system including a processor and memory, one or more feature maps from the visual information using one or more feature extractors; classifying, by the computing system, the object by supplying the one or more feature maps to a complex classifier to compute a classification of the object, the complex classifier including: a plurality of simple classifiers, each simple classifier of the plurality of simple classifiers being configured to compute outputs representing a characteristic of the object; and one or more logical operators configured to combine the outputs of the simple classifiers to compute the classification of the object; and outputting, by the computing system, the classification of the object as a result of the automatic visual inspection.

A system and method for sequence extraction using screenshot images to generate a robotic process automation workflow is disclosed. The system and method include capturing a plurality of screenshots of steps performed by a user on an application using a processor, storing the screenshots in memory, determining action clusters from the captured screenshots by randomly clustering actions into an arbitrary predefined number of clusters, wherein screenshots of different variations of a same action is labeled in the clusters, extracting a sequence from the clusters, and discarding consequent events on the screen from the clusters, and generating an automated workflow based on the extracted sequences.

An information processing apparatus includes a processor configured to extract a mark specified in advance from an image of a document; and acquire a character string by performing character recognition on a region located in a particular direction with respect to a position of the mark, the direction being associated in advance with the mark.

Disclosed herein is a software technology for facilitating an interactive conversational session between a user and a digital conversational character. For instance, in one aspect, the disclosed process may involve two primary phases: (1) an authoring phase that involves a first user accessing a content authoring tool to create a given type of visual conversation application that facilitates interactions between a second user and a digital conversational character in an interactive conversational session, and (2) a rendering phase that involves the second user accessing the created visual conversation application to interact with the digital conversational character in an interactive conversational session. In one implementation, accessing the created visual conversation application may involve detecting an object and identifying information associated with the detected object. The digital conversational character involved in the interactive conversational session may be superimposed onto a real-world environment.

A term weight determination method includes: obtaining a video and video-associated text, the video-associated text including at least one term; generating a halfway vector of the term by performing multimodal feature fusion on the features of the video, the video-associated text and the at least one term; and generating the weight of the at least one term based on the halfway vector of the at least one term.

A video text tracking method and an electronic device are disclosed. In the method, a text line region is split into sub-regions, the sub-regions are tracked and then processed, and processed sub-regions are combined into a new text line. The technical solutions provided in this application are not only applicable to a straight-line text scenario or a curved text scenario, but also present a good tracking effect for a deformable text line.

Asset error remediation is provided. Risk and classification of an asset error are analyzed to prioritize asset error remediation for an asset based on risk criticality, risk context, and vulnerability level corresponding to the asset by detecting suspicious behavior and risk exposure to the asset in a heterogeneous distributed computing environment using artificial intelligence. A priority of the asset error remediation is determined to fix the asset within the heterogeneous distributed computing environment based on the risk and the classification of the asset error. A set of action steps is performed to fix the asset within the heterogeneous distributed computing environment based on the priority of the asset error remediation.

The present disclosure is a part identification and location system that has a server and a handheld device, and the handheld device is communicatively coupled to the server via a network. Further, the system has a handheld device processor that displays a plurality of graphical user interfaces to the handheld device and receives data from a user of the handheld device identifying a system, subsystem, or part that the user desires to purchase. Additionally, a server processor searches for the desired system, subsystem, or part on a plurality of part databases, locating one or more parts that match the system, subsystem, or part the user desires. The handheld device processor displays a list of the system, subsystems or parts located, receives data indicating which system, subsystem, or part the user desires to purchase, and receives payment data for purchasing the system, subsystem, or part.

According to an embodiment, an information processing apparatus includes a second recognition unit, an information processing unit, and an information output unit. The second recognition unit recognizes, by second recognition processing, a destination of an article with the destination. not recognized by first recognition processing by a first recognition unit. The information processing unit generates recognition processing information proving that the second recognition processing has been executed by the second recognition unit. The information output unit outputs the recognition processing information.

To provide an information processing apparatus, an information processing method, and a program that make it possible to suitably provide three-dimensional property information. A floor-plan identifying unit that generates floor plan information on the basis of a floor plan image and a model generating unit that generates a three-dimensional model using the floor plan information are included. The floor-plan identifying unit includes: a line-segment detecting unit that detects a line segment corresponding to a wall on a floor plan, a segmentation processing unit that identifies a room region corresponding to a room on the floor plan, a character recognizing unit that recognizes a character string included in the floor plan image, a fixture detecting unit that detects a fixture sign included in the floor plan image, and an integration unit that identifies a type of room of the room region and complements a room structure. The model generating unit includes an estimating unit that estimates a scale of the floor plan and a generating unit that generates a three-dimensional model of the real-estate property on the basis of the floor plan identified from the floor plan information, the scale, and an estimated ceiling height.