Disclosed herein are charged particle microscopy (CPM) support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, a CPM support apparatus may include: first logic to cause a CPM to generate a single image of a first portion of a specimen; second logic to generate a first mask based on one or more regions-of-interest provided by user annotation of the single image; and third logic to train a machine-learning model using the single image and the one or more regions-of-interest. The first logic may cause the CPM to generate multiple images of corresponding multiple additional portions of the specimen, and the second logic may, after the machine-learning model is trained using the single image and the one or more regions-of-interest, generate multiple masks based on the corresponding images of the additional portions of the specimen using the machine-learning model without retraining.

A method for tracking objects in an area is provided. The method comprises receiving a camera frame providing a view of at least one section of the area, selecting an object in the received camera frame and labelling the selected object to associate one or more tags with each of the one or more tags being assigned a value. The method further comprises maintaining a library of values assigned to the one or more tags and providing a user interface to allow an operator to select at least one value from the library of values assigned to the one or more tags to filter the corresponding one or more objects associated with the said at least one tag having the selected at least one value, for tracking the corresponding one or more objects in the area.

A method and system for processing an image is described. For example, the method comprises detecting a plurality of objects within an in input image; identifying dimensions of a display on which the input image is to be displayed; cropping the input image to obtain a cropped image which matches the identified dimensions, wherein the cropped image includes at least one of the plurality of detected objects; obtaining a list of missing objects which are not visible in the cropped image and which were detected in the input image; outputting a representation of each missing object in the list of missing objects to be displayed together with the cropped image; generating an updated image comprising the representation of at least one missing object and which matches the identified dimensions; and outputting the updated image to be displayed on the display.

This application discloses a method and an apparatus for selecting a face image, a device, and a storage medium and relates to the field of artificial intelligence technologies. The method includes detecting, after a frame of face image is obtained, whether the face image meets a preliminary quality screening condition; determining, in response to a first face image meeting the preliminary quality screening condition, an overall quality score of the first face image, the overall quality score representing overall quality of the face image; and transmitting the first face image to a face recognition process in response to the overall quality score of the first face image being greater than a level-one threshold.

An information processing apparatus that performs a control for detecting a person from an image captured by an image capturing, detecting a first direction based on a gesture performed by the person, specifying, as an indicated region, a background information region including a background information in an image captured by the image capturing unit, in a case where the background information region and the first direction intersect; and adjusting an angle of view of the image capturing such that the person and the indicated region are included in the angle of view, wherein in a case where a plurality of background information regions in the image and the first direction intersect, the indicated region is specified corresponding to a background information region that fulfills a predetermined condition from among the plurality of background information regions.

Machine learning-based multi-view video conferencing from single view video data, including: identifying, in video data, a plurality of objects; and generating a user interface comprising a plurality of first user interface elements each comprising a portion of the video data corresponding to one or more of the plurality of objects.

Aspects of the subject disclosure may include, for example, embodiments that include receiving video content over a communication network, and determining a point of interest in relation to a presentation of the video content via equipment utilized by a user. Further embodiments can include identifying an object in the video content according to the point of interest, and obtaining information associated with the object. Additional embodiments can include generating first augmented reality content based on the video content and the information associated with the object, and providing the first augmented reality content to a communication device. The communication device presents the first augmented reality content. Other embodiments are disclosed.

Techniques are described for capturing data from a digital document through the use of targeted user feedback regarding the position(s) of particular data field(s) in the document. Implementations enhance the speed and accuracy of data capture from documents and/or images of documents by providing a helpful and intuitive set of controls to enable the end user to indicate the position(s) of field(s) on a document. Through specification of the position of the field in the document, implementations may isolate the portion of the document where data extraction is to be performed to determine the associated value of the field. Any suitable number of field values may be extracted from the document in this manner, based on positions indicated by the user using the provided control(s). In some implementations, one or more actions may be automatically performed based on the extracted data, such as automated bill payment actions.

A wearable device for use in immersive reality applications is provided. The wearable device includes eyepieces to provide a forward-image to a user, a first forward-looking camera mounted on the frame and having a field of view, a processor configured to identify a region of interest within the forward-image, and an interface device to indicate to the user that a field of view of the first forward-looking camera is misaligned with the region of interest. Methods of use of the device, a memory storing instructions and a processor to execute the instructions to cause the device to perform the methods of use, are also provided.

Techniques image suitability determination to generate augmented reality/virtual reality (AR/VR) digital content are described. A two-dimensional digital image is received. Using machine-learning, a determination as to whether an object captured by the two-dimensional digital image is suitable for generating AR/VR digital content for display in an AR/VR environment is made. If the object is suitable, an indication is provided and an option to view the object in an AR/VR environment is provided. If the object is not suitable, a suggestion indicating why the object as captured is not suitable and/or how to correct the capture of the object in a subsequent digital image such that it is suitable for generating AR/VR digital content.