A vehicle control device according to an embodiment of the present invention includes an interface unit connected to a display and a camera within a vehicle; a processor receiving an image obtained by the camera through the interface unit and evaluating the received image based on a plurality of features, wherein the processor evaluates the image depending on whether the plurality of features satisfies a condition in which a driver sitting in the vehicle is recognizable; and a memory storing malfunction information of the camera corresponding to an evaluation result of the image. The processor controls the display to display malfunction information of the camera if the evaluation result of the image is determined to be poor.

A method for operating an adaptive gateline may include detecting a patron approaching a gateline. The method may include determining whether the gateline should be operated in a standard mode or in a modified mode based at least in part on data from one or more sensors. The method may include operating the gateline in the standard mode or in the modified mode based on the determination. In the modified mode a barrier of the gateline operates to provide one or both of extra time or additional space for the patron to pass through the gateline relative to the standard mode.

A sampling robot, a robot system for goods sampling and detection and a detection method are disclosed. The image collection unit takes photos of a sample. The refrigeration unit stores the sample at a preset temperature. The biometric information collection unit collects the biometric information of the operator. The intelligent mobile unit moves according to a planned path. The control unit provides destination information to the intelligent mobile unit and judges whether the current sample is a sample to be detected, and judges the biometric information of the operator.

A method for automatically determining exposure settings for an image acquisition system comprises maintaining a plurality of look-up tables, each look-up table being associated with a corresponding light condition and storing image exposure settings associated with corresponding distance values between a subject and the image acquisition system. An image of a subject is acquired from a camera module; and a light condition occurring during the acquisition is determined based on the acquired image. A distance between the subject and the camera module during the acquisition is calculated. The method then determines whether a correction of the image exposure settings for the camera module is required based on the calculated distance and the determined light condition; and responsive to correction being required: selects image exposure settings corresponding to the calculated distance from the look-up table corresponding to the determined light condition; and acquires a new image using the selected image exposure settings.

Devices and methods are provided for using an interactive media to select content based on a user emotion. The device may receive user data associated with presentation of first content at a first time. The device may determine, based on the user data, a first emotion state of a user. The device may determine a target emotion state for the user at a second time. The device may determine a difference between the first emotion state and the target emotion state. The device may determine, based on the difference, a function associated with content determination. The device may determine, based on the function, second content for presentation to the user.

A method and an apparatus for identity verification, an electronic device, a computer program, and a storage medium include: obtaining a first image of a document, where the first image contains a first face image; obtaining a second image containing a face of a to-be-verified person; performing face comparison on the first image and the second image to obtain a first comparison result; and obtaining an identity verification result according to the first comparison result.

A layout analysis method, an electronic device, and a non-transitory computer-readable storage medium are provided. The layout analysis method includes: obtaining coordinate information of a plurality of text lines in an image; creating a layout model of the image according to the coordinate information; analyzing a layout structure of the text lines based on the layout model; and determining an order of the text lines relative to each other based on the layout structure.

An embodiment includes determining an experiential state of a first user participating in a mixed-reality experience. The embodiment also includes creating a first driver model that maps a relationship between the experiential state of the first user and a parameter of the mixed-reality experience. The embodiment also includes aggregating the first driver model with a plurality of driver models associated with experiential states and parameters of respective other users. The embodiment also includes creating a first cohort experience model using the aggregated driver models. The embodiment also includes deriving a first cohort experience parameter for the first cohort experience model. The embodiment also includes initiating an automated remedial action for participants in the mixed-reality system being associated with the first cohort experience model and the first cohort experience parameter.

Disclosed herein are systems and methods for classifying a tympanic membrane by using a classifier. The classifier is a machine learning algorithm. A method for classifying a tympanic membrane includes steps of: receiving, from an interrogation system, one or more datasets relating to the tympanic membrane; determining a set of parameters from the one or more datasets, wherein at least one parameter of the set of parameters is related to a dynamic property or a static position of the tympanic membrane; and outputting a classification of the tympanic membrane based on a classifier model derived from the set of parameters. The classification comprises one or more of a state, a condition, or a mobility metric of the tympanic membrane.

An image recognition method includes: performing image detection on an image to be recognized to obtain at least one face detection result, at least one operational part detection result, and at least one trunk detection result, each face detection result including one face bounding box, each operational part detection result including one operational part bounding box, and each trunk detection result including one trunk bounding box; respectively combining each of the at least one trunk detection result with each face detection result, to obtain at least one first result combination; respectively combining each trunk detection result with each operational part detection result, to obtain at least one second result combination; and associating the at least one first result combination with the at least one second result combination, to obtain an association result.