A technique manages collaborative web sessions (CWS). The technique receives graphical content of a CWS. The technique translates a set of portions of the graphical content into text output. The technique provides the text output to a set of text application services. The set of text application services associate the text output with the CWS.

Disclosed in some examples are methods, systems, devices, and machine-readable mediums that provide an ability for an entity to independently commence, advance, and complete a resource allocation offer in a matter of minutes as opposed to weeks or months after an automated resource pre-committal process. The system, using and incorporating machine learning techniques and algorithms, may have several phases, including a setup phase, resource pre-committal phase, an import phase, a processing phase, a verification phase, a resource allocation offer phase, and a resource allocation phase in which the system allocates resources to a vendor.

A method of sorting baggage at an airport, the method comprising: acquiring a digital image of an identification label for identifying a piece of baggage, the label including an identification code designed to correspond to a set of items of data from a first database compiled as the baggage is being checked in; the method further comprising the following steps: retrieving information that is printed on the label from the image; comparing the information with data that is recorded in a local second database at the airport before the label is printed, the second database being distinct from the first database, the data from the second database being representative of a list of flights to or from the airport; and, in response to a match being detected, transmitting data representative of a flight number corresponding to the piece of baggage to a conveyor system.

One or more highlights of a video stream may be identified. The highlights may be segments of a video stream, such as a broadcast of a sporting event, that are of particular interest to one or more users. According to one method, at least a portion of the video stream may be stored. The portion of the video stream may be compared with templates of a template database to identify the one or more highlights. Each highlight may be a subset of the video stream that is deemed likely to match the one or more templates. The highlights, an identifier that identifies each of the highlights within the video stream, and/or metadata pertaining particularly to the one or more highlights may be stored to facilitate playback of the highlights for the users.

A computer-implemented method of transcribing an audio stream can include transcribing the audio stream using a first transcribing instance having a first predetermined transcription size that is smaller than the total length of the audio stream. The first transcribing instance can provide a plurality of consecutive first transcribed text data snippets of the audio stream and the size of the first transcribed text data snippets can respectively corresponding to the first predetermined transcription size. The audio stream can also be transcribed using at least a second transcribing instance having a second predetermined transcription size that is smaller than the length of the audio stream. The second transcribing instance can provide a plurality of consecutive second transcribed text data snippets each corresponding to the second predetermined transcription size.

An auto-rotation module having a single-layer neural network on a user device can convert a document image to a monochrome image having black and white pixels and segment the monochrome image into bounding boxes, each bounding box defining a connected segment of black pixels in the monochrome image. The auto-rotation module can determine textual snippets from the bounding boxes and prepare them into input images for the single-layer neural network. The single-layer neural network is trained to process each input image, recognize a correct orientation, and output a set of results for each input image. Each result indicates a probability associated with a particular orientation. The auto-rotation module can examine the results, determine what degree of rotation is needed to achieve a correct orientation of the document image, and automatically rotate the document image by the degree of rotation needed to achieve the correct orientation of the document image.

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.