7 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.

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.