A method for mapping an environment by an electronic device is described. The method includes obtaining a set of sensor measurements. The method also includes determining a set of voxel occupancy probability distributions respectively corresponding to a set of voxels based on the set of sensor measurements. Each of the voxel occupancy probability distributions represents a probability of occupancy of a voxel over a range of occupation densities. The range includes partial occupation densities.

A system maintains a knowledge layout to support the building of event response recommendations. Meta-graph patterns may be used to determine semantic relatedness between events and actions in response. Event-action node pairs are then constructed.

A device includes memory and a processor. The device receives biometric information. The device receives location information. The device analyzes the received biometric information with stored biometric information. The device analyzes the received location information with stored location information. The device determines whether the received biometric information matches the stored biometric information. The device determines whether the received location information matches the stored location information. The device sends an electronic communication that indicates whether the received biometric information matches the stored biometric information and whether the received local information matches the stored location information.

In authentication using sensor information, both reduction of processing burdens and assurance of security can be achieved.

Provided is an information processing device including an authentication unit configured to authenticate a user on the basis of collected sensor information, and the authentication unit authenticates the user on the basis of a single feature quantity extracted on the basis of sensor information collected by at least two sensors and a single registered feature quantity extracted on the basis of sensor information collected in advance by the at least two sensors.

There are provided a learning apparatus, a learning method, and a program that enable, by using one type of device data, learning of a plurality of models using different data formats. A learning data acquiring section (36) acquires first data that is first-type device data. A first learning section (42) performs learning of a first model (34(1)) in which an estimation using the first-type device data is executed by using the first data. A learning data generating section (40) generates second data that is second-type device data the format of which differs from the format of the first-type device data on the basis of the first data. A second learning section (44) performs learning of a second model (34(2)) in which an estimation using the second-type device data is executed by using the second data.

Computer-implemented machines, systems and methods for managing missing values in a dataset for a machine learning model. The method may comprise importing a dataset with missing values; computing data statistics and identifying the missing values; verifying the missing values; updating the missing values; imputing missing values; encoding reasons for why values are missing; combining imputed missing values and the encoded reasons; and recommending models and hyperparameters to handle special or missing values.

Methods, devices, and systems for identifying charging devices are provided. In one aspect, a method of identifying a charging device include: capturing an infrared image and a depth image of a current field of view with a depth camera; determining, according to the infrared image, that there are one or more suspected charging device areas that satisfy first specified conditions; determining, according to the depth image, that there is a target charging device area whose height relative to a depth camera is within a specified range in the one or more suspected charging device areas; and identifying the charging device according to the target charging device area. The first specified conditions indicate that a gray-scale value of each of pixels in an area is greater than a second specified value, and a number of the pixels in the area is greater than a third specified value.

Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.

The present disclosure relates to an information processing apparatus and method, an electronic device and computer readable medium. According to an embodiment, an information processing apparatus includes processing circuitry configured to compare environment data acquired by a user equipment with reference data; determine, based on the comparison, an adjustment for an acquisition manner of the environment data; and perform a control to notify the user equipment of indication information related to the adjustment.

A dynamic imaging system is disclosed. The dynamic imaging system may comprise one or more imager, one or more input device, a controller, and/or a display. Each imager may be operable to capture a video stream having a field of view. In some embodiments, the controller may articulate the imager or crop the field of view to change the field of view in response to signals from the one or more input devices. For example, the signal may relate to the vehicle's speed. In other embodiments, the controller may apply a warp to the field of view. The warp may be applied in response to signals from the one or more input devices. In yet other embodiments, video streams from one or more imagers may be stitched together by the controller. Further, the controller may likewise move the stitch line in response to signals from the or more input devices.