10 results about "Machine recognition" patented technology

The present application belongs to the technical field of data extraction, and discloses an information extraction method and device, an electronic device and a storage medium. The present application adopts a machine recognition and processing mode to automatically extract the content in pictures and documents, and performs error correction processing on the extracted content after extraction, so as to obtain an information keyword set with high accuracy. Compared with manual extraction, the present method is not only efficient, but also reduces labor costs, and is suitable for large-scale application and promotion in the field of information extraction technology.

This application discloses a batch calibration method for multi-workpiece weld seam scanning trajectories, belonging to the field of machine recognition weld seam technology. The method includes the following steps: acquiring the original point cloud data of all workpieces through a line laser sensor; processing the original point cloud to obtain workpiece point cloud data, and performing filtering and downsampling processing; performing coarse registration to obtain the initial rigid body transformation relationship; performing fine registration to obtain the optimal rigid body transformation matrix; mapping the predefined weld seam scanning path in the template coordinate system to the actual workpiece coordinate system to generate a working trajectory that can drive the execution device; immediately starting the welding operation process of the first workpiece after generating the scanning path of the first workpiece; simultaneously performing the registration and path calibration process sequentially on the subsequent workpiece point clouds, realizing the parallelization of processing and calculation, and effectively solving the core pain point of batch calibration of weld seam scanning paths for similar workpieces.

An operation management device includes a machine tool detection unit which detects industrial machines from videos from cameras based on registered feature points of the industrial machines, a varying point detection unit which detects, from the videos, time-varying feature points of the detected industrial machines and change times, and an individual machine recognition unit which recognizes the individual industrial machines based on the time-varying feature points and change times. The operation management device also includes a camera parameter calculation unit which calculates camera parameters of each camera, a machine distance calculation unit which calculates the distances between the feature points and the cameras based on the camera parameters, and a layout diagram creation unit which creates a layout diagram of icons of the industrial machines from the calculated distances and locations and three-dimensional coordinates of the center of the lens of each camera.

A kind of machine vision rate distortion encoding method of license plate recognition task, by obtaining license plate image data set, extracting saliency feature, modulation adaptive quantization parameter, rate distortion optimization and fast division, license plate recognition step composition.The present application extracts background, vehicle, license plate three-level area feature using target detection network, calculates normalized perception intensity, uses hyperbolic tangent function to dynamically adjust the quantization parameter of coding unit, and optimizes the coding division process by combining subsection depth constraint strategy.Solves the technical problems of license plate character target blur and machine recognition rate decline under the conditions of application of video coding on unmanned aerial vehicle and limited code rate, reduces the encoding code rate and computational complexity, preserves the high-frequency microscopic details of license plate characters, improves the recognition accuracy and robustness of machine vision.The present application has the advantages of balancing code rate, low computational complexity, high license plate recognition accuracy, and can be used for unmanned aerial vehicle long-distance license plate recognition.

This application discloses a defense method and related equipment based on human-machine recognition, relating to the field of data processing technology. The method includes: responding to a human-machine recognition command, acquiring user operation data; performing human-machine recognition based on a preset human-machine recognition strategy and the user operation data; and obtaining a human-machine recognition result. The human-machine recognition result includes manual input and script input. The preset human-machine recognition strategy is constructed based on a preset lightweight model. If the human-machine recognition result is script input, defense is implemented. This application leverages the different trajectory features corresponding to manual input and script input, using trajectory features extracted from user operation data and a preset lightweight model to accurately determine whether the trajectory during the verification process is script input, thereby flexibly implementing defense.

A computer-implemented method includes receiving, by one or more processors, a set of structured records containing clinical information associated with one or more patients; extracting, by the one or more processors, a set of medical entities from the clinical information; determining, by the one or more processors, relationship strengths between pairs of the medical entities; and configuring, by the one or more processors, a computer-readable memory with a knowledge graph data structure in which nodes of the knowledge graph data structure represent the medical entities and the nodes are related to one another in the knowledge graph data structure based on the relationship strengths.

This invention discloses a web crawler detection system based on application scenarios, including a crawler detection platform. The crawler detection platform comprises a user analysis unit, a human-machine recognition unit, a secondary verification unit, a space development unit, and a reality integration unit. This invention relates to the field of web crawler detection technology. This application scenario-based web crawler detection system divides the enterprise network into different application scenarios according to their uses. Based on these application scenarios, it performs triple malicious crawler identification, achieving a more comprehensive screening of malicious crawlers. Simultaneously, it provides registered users with personal spaces, offering convenience and effectively avoiding false positives on genuine users, thus improving user experience. Furthermore, by combining network information related to the application scenarios to manage personal spaces, it greatly enhances the flexibility of malicious crawler detection while effectively locating abnormal parts of the enterprise network, providing powerful assistance for the operation and management of the enterprise network.

This disclosure provides a proofreading task detection method, apparatus, electronic device, and storage medium. The method includes: determining reference attribute information for a target proofreading task, the reference attribute information including at least one of first attribute information, second attribute information, and third attribute information; the first attribute information indicating the text correction rate when performing text correction on at least one preset erroneous text corresponding to the target proofreading task; the second attribute information indicating the text correction omissions when performing text correction on multiple second reference texts; and the third attribute information indicating the text correction doubts when performing text correction on multiple second reference texts; and performing proofreading task quality detection on the target proofreading task based on the reference attribute information. This disclosure can detect low-quality proofreading tasks that are careless, inattentive, or blindly retain machine-recognizable characters during the execution of proofreading tasks.

The application discloses a somatic intelligent visual language action model for hinge joint operation, which comprises an image text multi-modal feature matching module, a visual language model, an object key point prediction and gripper pose prediction module, an object motion trajectory prediction module and an adaptive strategy selection module. The model is fused with a visual-language-action architecture, image text multi-modal technology, a visual language model and a group relative strategy optimization method, realizes the identification of home object operation key points, the estimation of mechanical arm poses and the prediction of motion trajectories, and thus completes the accurate operation of objects. The application selects three types of high-frequency interactive objects, i.e. washing machines, refrigerator doors and drawers, for testing. The washing machine recognition accuracy is improved from 78% of a traditional algorithm to 96%; the refrigerator door recognition accuracy is improved to 76%; and the drawer recognition accuracy is improved from 71% to 78%, which greatly improves the understanding and operation precision of the somatic housekeeper for hinge objects.

The application discloses a kind of based on deep learning multilayer multi-pass welding process processing method, belong to machine identification weld technical field, the method includes the following steps: to the welding slope original three-dimensional point cloud executes filtering optimization operation;Based on deep learning algorithm, the point cloud after pre-processing is handled with semantic segmentation, identifies the structure area of slope and distinguishes slope type;Based on segmentation result, plane fitting is carried out to the slope elevation point cloud, judges elevation according to the proportion of fitting point cloud, and calculates the slope angle in combination with slope type;According to the type of slope and the geometric type of elevation, the corresponding positioning strategy is matched, and the reference weld track is determined;According to the input welding layer number and pass number, in combination with slope angle and base weld, the offset track of each welding pass relative to base weld is calculated, and multilayer multi-pass welding track is generated;With model-driven full-path automatic generation replaces empirical manual setting, realize the full-process automation path planning from backing welding to cover welding.