8 results about "Block sorting" patented technology

The invention relates to the technical field of data monitoring, and particularly discloses a deep foundation pit multi-source heterogeneous data intelligent monitoring system based on end-cloud collaboration. The system comprises a collaboration center, and the collaboration center comprises a multi-source feature confirmation end, a node block classification end, a block feature verification end and an optimization logic output end. A transmission protocol is identified and monitoring frequency is locked through a multi-source feature confirmation end, monitoring nodes using the same transmission protocol are divided into the same block node through a node block classification end, and block sorting combination is optimized through a block feature verification end. An optimal combination is output through an optimization logic output end to guide monitoring time and frequency adjustment; the problems of scheduling conflicts and waiting time consumption among different protocol blocks are solved, global optimal acquisition is realized, system operation energy consumption is reduced, and smoothness and stability of collaborative acquisition of multiple protocol blocks are guaranteed.

The invention discloses a real estate data processing method and device, electronic equipment and a storage medium, and the method comprises the steps: inputting a real estate right certificate image into a real estate right certificate recognition model, carrying out the semantic segmentation of the real estate right certificate image in a semantic segmentation network, and obtaining a plurality of image regions, geometric information and semantic tags; extracting text blocks in the image area in the text block sorting network, sorting the text blocks according to geometric information to obtain a text block sequence, extracting text contents from the text blocks in the text block sequence in the text recognition network, filling the text contents and semantic tags into a structured data template to obtain structured real estate data, and storing the structured real estate data in the text recognition network. According to the method, the structured real estate data is encrypted and then stored in the database, so that the structured real estate data is obtained by extracting the text content from the real estate certificate through the real estate certificate identification model and filling the text content into the structured data template, manual input is not needed, and the input efficiency and accuracy of the real estate data are improved.

The invention discloses an automatic building block sorting method and system based on machine vision, and relates to the field of building block sorting detection.The intelligent and precise building block sorting is realized through multi-module cooperation: firstly, a type mapping model is constructed based on image data, and rapid type identification and single block sorting of to-be-sorted building blocks are realized; for the composite building blocks, through collaborative operation of double mechanical arms and dynamic clamping optimization, in combination with convex block distribution judgment and a success rate mapping model, through dynamic adjustment of clamping force and real-time evaluation of the splitting success rate, the intelligence and reliability of the building block sorting system are remarkably improved, efficient splitting and sorting of building blocks of different structures are achieved, and the working efficiency is improved. The problem of building block damage or splitting failure caused by traditional fixing force is avoided; the whole process forms a detection-recognition-disassembly-sorting closed loop, the sorting efficiency and accuracy are remarkably improved, meanwhile, the manual intervention requirement is reduced, and the method is particularly suitable for automatic processing of complex building block combinations.

Sorting data in memory is a fundamental computation that facilitates a wide range of search and query problems, aids in the construction and manipulation of data structures, and can improve the spatial and temporal locality of data and computation. Oftentimes, merge-based designs are used for sorting data, where a block sorting pass is performed followed by merging passes that produce increasingly larger sorted sublists until only a single list remains. While conventional merge-based designs can support multiple (K) merge operations in a single pass, a balance must be struck since there exists a point where K-scaling is no longer profitable. The present disclosure provides an alternative merge-based design in which data is merged using a single feed-forward data path.

The application discloses a layout block sorting method, belongs to the field of optical character recognition, and helps to improve the efficiency of workflow execution. The method comprises the following steps: cutting a target image to obtain spatial information of at least two layout blocks to be sorted, and generating a layout block spatial information sequence; performing feature extraction and coding processing on the layout block spatial information sequence through an encoding network module of a pre-trained neural network model, obtaining a feature coding sequence corresponding to the layout block spatial information sequence, and each layout block feature vector in the feature coding sequence corresponds to a layout block to be sorted; and performing sorting prediction on the feature coding sequence through a decoding network module of the neural network model, and obtaining a sorting result of each layout block to be sorted. The method learns the complex mapping relationship between the spatial information of the layout block and the layout block sorting position through the neural network model, and is applied to the layout block sorting, so that the accuracy of the layout block sorting is improved.

The application discloses a kind of based on machine vision's building block automatic sorting method and system, it is related to building block sorting detection field, the present application realizes the intellectualization and precision of building block sorting by multi-module cooperation: first, type mapping model is constructed based on image data, realize the quick type identification of to be sorted building block and single piece sorting;For composite building block, through double mechanical arm cooperative operation and dynamic clamping optimization, in combination with bump distribution determination and success rate mapping model, by dynamically adjusting clamping strength and real-time evaluating split success rate, the intellectualization and reliability of building block sorting system are significantly improved, realize the efficient split and sorting of different structure building block, avoid the problem of building block damage or split failure caused by traditional fixed intensity;The whole process forms detection-identification-disassembly-sorting closed loop, significantly improve sorting efficiency and accuracy, while reducing the need for manual intervention, especially suitable for complex building block combination automatic processing.

The invention discloses a UE scene localization migration and reconstruction method and system based on Gaussian sputtering, and belongs to the technical field of digital scene construction and virtual reality. Track planning is carried out through a virtual camera matrix, a high-definition image sequence is output, camera parameters are extracted synchronously, left and right hand coordinate system conversion is realized by adopting a coordinate system mapping algorithm, and the real-time migration and reconstruction of the UE scene are realized. An initial point cloud is generated in combination with denoising sharpening processing and the depth map, and three-dimensional reconstruction convergence is accelerated; constructing an initial model by using a spherical harmonic function and a covariance matrix, reducing errors by optimizing renderer iteration, exporting a point cloud format, and constructing a real-time rendering framework by means of block sorting and an Alpha mixing technology; and parameters are dynamically adjusted for performance fluctuation, point cloud density information is fused, light and shadow consistency is ensured, and finally a stable high-fidelity scene model is formed. According to the method, the modeling precision and the rendering efficiency of the virtual reality scene are remarkably improved, and reliable support is provided for interactive application.

The invention relates to the technical field of parameter configuration, in particular to a programmable audio parameter configuration system which comprises a label boundary extraction module, a semantic field binding module, a structure block sorting module, a configuration parameter path matching module and a control command writing module. According to the method, the voice instruction text is automatically extracted, the effective statement boundary is recognized, functional semantic classification of the configuration command is achieved by combining annotation structure analysis, command and physical resource mapping is completed according to the component configuration path in the unified extensible firmware interface, and a configuration block set capable of being directly executed is formed; a controller command interface is called to complete configuration data real-time write-in and write-in result comparison, each command change field is recorded in the process, a filing track is formed, automatic closed-loop processing of the whole process from command extraction to write-in response is achieved, manual intervention and format errors are avoided, the configuration efficiency and parameter verification precision are improved, and the method is suitable for large-scale popularization and application. The cross-role cooperation frequency is reduced, and the audio debugging response speed is improved.