12 results about "Automatic localization" patented technology

The invention relates to the technical field of metal material quality detection, and discloses a metal material surface defect detection method, device and equipment and a storage medium, and the method comprises the steps: obtaining a standard three-dimensional point cloud template and actual measurement point cloud data of the surface of a target metal material; preprocessing the actually measured point cloud data to obtain preprocessed actually measured point cloud data; performing space alignment on the preprocessed actually measured point cloud data and a standard three-dimensional point cloud template based on a registration algorithm to obtain a registration result; residual data are generated according to the registration result, and candidate defect areas are identified from the residual data; and performing clustering analysis on the candidate defect area to obtain defect information of the surface of the metal material. According to the invention, the detection stability of the metal material and the recognition precision of small defects can be improved, automatic positioning and noise filtering of deformation defects such as gutter formation and bone formation are realized, and the detection rate and the detection intelligent level are remarkably improved.

A method may involve: receiving direction of arrival (DOA) data corresponding to sound emitted by at least a first smart audio device of the audio environment that includes a first audio transmitter and a first audio receiver, the DOA data corresponding to sound received by at least a second smart audio device of the audio environment that includes a second audio transmitter and a second audio receiver, the DOA data corresponding to sound emitted by at least the second smart audio device and received by at least the first smart audio device; receiving one or more configuration parameters corresponding to the audio environment, to one or more audio devices, or both; and minimizing a cost function based at least in part on the DOA data and the configuration parameter(s), to estimate a position and an orientation of at least the first smart audio device and the second smart audio device.

This invention relates to an automatic localization method, computer device, and system for ulcer fragments in intestinal capsule endoscopy videos. It establishes an automatic ulcer fragment localization network based on initial temporal boundary specifications, combined with policy gradients and evaluation. The network is trained using query image-reference video pairs. The network is input into the trained network and outputs ulcer fragments in the reference video associated with the query image. A computer device is implemented based on this method. The system uses an input unit to input query image-reference video pairs, a localization unit to execute the method and locate the ulcer fragments, and an output unit to output the results. This invention uses an image of an ulcer lesion of interest from an intestinal capsule endoscopy as the query image and a long intestinal capsule endoscopy video as the reference video. It analyzes the video using reinforcement learning, refines the temporal boundary through sequential decisions using start and end markers, and accurately locates fragments related to the query image, thus completing the video relocalization task.

Method for investigating a semiconductor circuit (2) comprising several semiconductor components (4-6) on a front face (2) of a circuit carrier (3), comprising the steps: - Obtaining image data (7) depicting the semiconductor circuit (1) or a test object (8) produced by machining the circuit carrier (3) of the semiconductor circuit (1) from a rear side (9) opposite the front side (2), and - automatic identification of a function (10) of at least one semiconductor component (4-6) and / or at least one group (11) of semiconductor components (4-6) and / or automatic localization (12) of at least one functional block (13) of the semiconductor circuit (1) implementing a given function and / or at least one contact pad (14) of the circuit carrier (3) in the image data (7) by evaluating the image data (7) using an image processing algorithm (15).

The invention discloses a method and system for analyzing vehicle accident time and place based on EDR and T-BOX fusion. The method comprises the following steps: collecting EDR data and T-BOX data of a suspicious vehicle; performing multi-dimensional feature matching on the EDR data and the T-BOX data to realize time alignment of the EDR data and the T-BOX data; searching a time point corresponding to the collision event and spatial data corresponding to the time point in the T-BOX data, preliminarily judging whether the suspicious vehicle is a suspected hit-and-run vehicle, and if so, entering a final judgment step; and analyzing the collision point location of the collision event by using the EDR data and the T-BOX data, comparing the collision point location with the collision point location in the vehicle accident record, and if the collision point locations are consistent with the collision point location in the vehicle accident record, determining that the suspicious vehicle is a suspicious accident vehicle and reporting a conclusion. According to the method, the EDR data and the T-BOX data are subjected to feature matching, and linear interpolation and cubic spline interpolation algorithms are combined, so that high-precision space-time automatic positioning of the collision event is realized, and vehicle responsibility determination is assisted.

In accordance with various embodiments, described herein are systems and methods for providing automated localization of software applications and graphical user interfaces. A software extension or add-in component operates both as a design tool, and as a runtime process, for purposes of localizing a software application or its graphical user interface, including the translation of user-visible strings displayable within graphical user interface elements. The translation manager can be used to automate the localization of a software application or workbook being developed, including during an extraction process, automatically identifying and associating user-visible strings with string keys. When the workbook is subsequently accessed and used at runtime, for example by a business user working within a particular region or language, the extension or add-in can use the string keys to automatically map prepared-translations to the graphical user interface elements, for use in localizing the software application.

A method may involve: receiving direction of arrival (DOA) data corresponding to sound emitted by at least a first smart audio device of the audio environment that includes a first audio transmitter and a first audio receiver, the DOA data corresponding to sound received by at least a second smart audio device of the audio environment that includes a second audio transmitter and a second audio receiver, the DOA data corresponding to sound emitted by at least the second smart audio device and received by at least the first smart audio device; receiving one or more configuration parameters corresponding to the audio environment, to one or more audio devices, or both; and minimizing a cost function based at least in part on the DOA data and the configuration parameter(s), to estimate a position and an orientation of at least the first smart audio device and the second smart audio device.

The invention discloses an AI-based multi-language front-end interface automatic localization method and system. The automatic localization method comprises the following steps: automatically loading and displaying a corresponding translation text according to language preference of a user; the language preference of the user is detected and recognized, and a translation version is automatically selected; automatically translating the application content by using machine learning and natural language processing technologies; adjusting the translation content according to the cultural background of the target language; the dynamic content is translated in real time; training the translation data based on a deep learning model; and multi-language resources are managed in a unified manner. And through an artificial intelligence technology, translation and localization of a multi-language front-end interface are automatically realized.

Embodiments included herein relate to a method, computer program product, and computing system for tire pressure monitoring. Embodiments of the present disclosure can include receiving amplitude and phase differences of a plurality of radio frequency (RF) signals between one or more TPMS sensors. Embodiments can also include comparing and monitoring the relative amplitude and phase differences of the plurality of RF signals between all of the TPMS sensors based on an automatic localization algorithm. Embodiments can also include distinguishing between a front of a vehicle and a back of the vehicle based on a statistical model. Embodiments can also include determining a rotational direction of all of the TPMS sensors on the vehicle based on information received from the statistical model in combination with data from sensor accelerometers.