4489 results about "Automatic processing" patented technology

The invention discloses a network equipment integrated monitoring method and system. The method comprises the following steps: collecting multi-source heterogeneous data, constructing a protocol compatible layer, and supporting multi-protocol adaptation; data fusion and intelligent analysis: constructing a dynamic topology, analyzing an equipment configuration file, and generating a network topological graph; performing time sequence prediction according to a root cause analysis model, and predicting an abnormal trend; mining association rules, analyzing historical data, and extracting fault association rules; constructing an equipment fault knowledge base under the assistance of a knowledge graph, and accelerating root cause positioning; self-adapting an alarm threshold, analyzing historical data distribution, and dynamically adjusting the threshold; visual decision making and automatic processing are carried out, a 3D topological map is provided, and layered display is supported; and performing fault grading processing, comprehensively calculating a fault influence degree score, mapping to a fault grade and a work order type according to an influence degree score interval, and formulating a dynamic work order generation rule. A protocol compatible layer is constructed by deploying a lightweight agent program, multi-protocol adaptation is supported, and various network devices can be fully covered.

A computer system for automatically handling and releasing funds for deposit items has a memory storing instructions that, when executed by a processor, cause the system to receive an image of a cheque received and scanned by an automated teller machine (ATM) for deposit into a first account of an institution associated with the ATM. The scanned image of the cheque is analyzed to identify an institution and account on which that cheque is drawn. If that account has sufficient available funds to cover the cheque, then the first account is credited in the amount of the cheque without placing a hold on any of the credited amount and funds of the account on which the cheque is drawn are encumbered in that same amount. After crediting the first account, an indication is provided that the funds are available (e.g., to withdraw). Related methods and computer-readable media are also disclosed.

The invention belongs to the field of artificial intelligence, and particularly relates to a bill information extraction method and system and a storage medium, and the method comprises the following steps: obtaining an electronic file containing a bill, and preprocessing the electronic file into an image file facilitating information extraction; extracting bill information in the image file by using a multi-modal large model and an OCR model, and outputting text information in a structured format; and analyzing, correcting and comparing text information respectively output by the multi-modal large model and the OCR model through the large language model, and performing fine tuning or cue word engineering guidance on the large language model for different tasks, so that an output result conforms to expectation. Compared with the prior art, the problems that in the prior art, OCR recognition accuracy is not high, and extracted information is incomplete are solved, the bill information processing speed is increased, the precision of the automatic processing process is greatly improved, and in financial, auditing and other related business scenes, the working efficiency and the data reliability are remarkably improved.

The invention provides an unstructured data automatic processing method and system based on deep learning, and relates to the technical field of data processing, and the method comprises the steps: obtaining unstructured data through an intelligent data collector, building a data feature fingerprint database, constructing a data quality evaluation model through an incremental learning algorithm, and carrying out the data standardization processing; extracting dominant features and recessive features by using a multi-layer cascade network structure and a self-attention mechanism, and constructing a feature association graph and a bidirectional reasoning channel; and performing rule matching and causal reasoning based on the domain knowledge base, and finally realizing automatic structuring of the unstructured data. According to the method, the automation degree and the accuracy of data processing are improved, the manual intervention cost is reduced, and the method has relatively high universality and expandability.

The invention discloses an automatic configuration method and system for an electric energy quality monitoring terminal supporting multiple protocols, and the method comprises the steps: obtaining a communication data packet through the establishment of communication connection between a terminal and a configuration system, and carrying out the protocol recognition through the combination of statistical characteristics and structural characteristics. According to the method, the hierarchical decision tree is innovatively adopted to identify the protocol characteristics, protocol family identification and specific protocol type determination are realized through the preset protocol mapping template, and a new protocol can be automatically processed. The system comprises a communication module, a feature extraction module, a protocol identification module, a configuration instruction module and an execution module, and all the modules work cooperatively to achieve automatic configuration of the terminal. The technical problems that the power quality monitoring terminal is difficult to configure in a multi-protocol environment, the protocol identification efficiency is low, and the new protocol adaptation is complex are solved.

The invention provides a complex task full-automatic processing method based on multi-agent cooperation and a related device, and relates to the technical field of artificial intelligence such as large language models, generative models, agents and task intelligent scheduling. The method comprises the following steps: interacting with a target user who puts forward an original task demand to obtain a complete task demand; the complete task demand is split into a plurality of sub-tasks at least comprising a complex sub-task, the complex sub-task refers to a sub-task needing at least two sub-agents to process according to a cooperation process, and a single sub-agent is used for processing a simple sub-task; issuing the complex sub-tasks to corresponding target execution intelligent units, and issuing the simple sub-tasks to corresponding target sub-agents; and summarizing sub-task execution results returned by each target execution intelligent unit and each target sub-agent. According to the method, the execution intelligent unit specially used for processing the complex sub-task is introduced, and the complex sub-task is processed more intensively according to the cooperation process through the at least two sub-agents contained in the execution intelligent unit, so that the task disassembling difficulty is reduced; and a better sub-task processing result can be obtained through the execution intelligent unit integrated by the multiple sub-agents.

The invention relates to a multi-modal large model-based low-slow small flight target identification and classification method and system, and aims at solving the problem of monitoring and identification of low-slow small flight targets in a complex scene. According to the method, various sensor data including visible light images, infrared images, radar signals, sound features and radio signals are fused, the multi-mode large model is used for processing and fusing data of different modes, combined features are extracted, efficient detection and classification of low-speed small targets are achieved, and the method has an automatic early warning function. The method has the advantages of real-time response, automatic processing and high recognition precision, and is suitable for low, slow and small flight target defense scenes such as airports, military bases and urban safety.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical treatment and health and the like, and discloses a multi-modal event data processing and collaborative circulation method, device, equipment and medium. Generating a stereoscopic scene model based on the event data file and positioning a target area, performing multi-modal fusion by combining a positioning result and non-spatial data of the event data file to generate a fusion analysis result and form a processing report, and constructing an auditing and judging item set containing a conditional strategy and an execution action to execute auditing and generate an auditing and judging result. And generating a collaborative circulation instruction set based on the processing report and the audit judgment result, and triggering execution through distributed message transmission to obtain an execution result. According to the method, through multi-modal data processing, three-dimensional scene modeling, cross-modal fusion analysis, rule-driven auditing and distributed execution, full-process automatic processing is realized, and the processing accuracy and efficiency are improved.

The invention discloses a government affair intelligent interaction and information extraction method and device, equipment and a medium, and relates to the technical field of digital government affair, digital cities, intelligent interaction and the like. The traditional manual item-by-item filling is converted into end-to-end automatic processing, so that the operation steps of a user are remarkably reduced, the filling burden of a hundred-item-level form is solved, and the filling efficiency is improved; and an ID voice corrector is adopted to realize three-layer progressive verification, so that the output ID offset of the multi-modal large model is effectively inhibited, the accurate mapping of field identifiers is ensured, and meanwhile, a lightweight knowledge graph is adopted to automatically capture logic rules among fields, interspecific compliance conflicts of government affair scenes are intercepted in real time, the logic error risk is reduced, and the filling accuracy is improved.

The invention relates to the technical field of machine vision and detection, in particular to a shoe pattern defect detection system based on the visual technology, which comprises an acquisition processing unit, a three-dimensional model unit, a defect detection unit and a defect processing unit. The three-dimensional model unit reconstructs an accurate shoe pattern three-dimensional model in sequence, the defect detection unit divides the model into a plurality of areas, calculates the average curvature, and accurately analyzes and judges the flatness defect degree by adopting a plane fitting algorithm based on a least square method and a curvature difference algorithm based on a sliding window; and the defect processing unit automatically processes the shoes with serious defects, so that high efficiency, accuracy and automation of shoe pattern defect detection are realized, and the quality detection level of shoe production is powerfully improved.

The invention relates to a financial bill management system and an implementation method thereof. The financial bill management system comprises a data acquisition module, an AI identification module, an auditing module, a cost reimbursement module, a report generation module and a data storage and backup module. According to the financial bill management system and the implementation method thereof, by introducing the AI recognition module, automatic recognition and classification of bill types are achieved, the requirement for manual operation is reduced, the working efficiency and accuracy are improved, the AI recognition module can automatically process bill information, the whole process from image preprocessing to final key information extraction is highly automatic, and the efficiency is high. The system is not limited to bill identification and classification, but also covers a plurality of functional modules such as data acquisition, auditing, expense reimbursement processing, report generation, data storage and backup and the like, and provides a one-stop solution for users. The image preprocessing unit can effectively remove image noise, correct inclined images, cut redundant parts and enhance image contrast and brightness.

The invention discloses a multi-agent computer-aided engineering and a computer-aided design method. CAE simulation and design optimization for the design of a complex product are high in threshold and difficulty. According to the method, autonomous planning and automatic execution of CAE simulation and CAD design optimization tasks are realized by using a multi-agent technology based on a large language model. A user interacts with the multi-agent system in the modes of text input, voice, a graphical user interface and the like, the multi-agent system autonomously plans workflow steps according to the requirements of the user, all agents cooperatively execute the working steps in a labor division mode, CAE and CAD software is called to execute simulation and design change, CAE and CAD result data are read and analyzed, the task completion condition is evaluated, and the task completion condition is evaluated. And the task can be re-planned if necessary. The system can automatically process error information, and can notify a user to process when user intervention is needed. The performance of the system can be improved through fine tuning of a large language model and retrieval enhancement generation technology.

The invention relates to the technical field of front-end development, in particular to an application fusion method based on a micro-front-end technology, which comprises the steps of sub-application registration, state management and synchronization, dynamic routing and navigation, cross-platform compatibility and adaptive design, resource optimization and loading strategy, performance monitoring, fault processing and the like. Registration and management of a plurality of sub-applications are realized through a uniform interface specification, a distributed state management mechanism is adopted to update and synchronize a global state, a dynamic routing system loads and renders the sub-applications as required according to user operation, and a cross-platform compatible design ensures consistent experience on different devices. According to the resource loading strategy, pre-loading and lazy loading are carried out by intelligently predicting user behaviors, unnecessary resource consumption is reduced, and the performance monitoring module monitors the running state of the system, automatically processes exceptions and provides a fault recovery mechanism. According to the method, the performance and the cross-platform adaptation capability of the micro-front-end application are effectively improved, and the method is suitable for development and deployment of complex enterprise-level applications.

Disclosed is an outdoor mobile robot manipulator for the automatic handling of railway inter box connectors (IBC) in an intermodal rail yard. The manipulator includes a dual-mode adaptive suspension for protection of the robotic arm and end-effector against shock and vibration, a universal fingerless gripper capable of manipulating main types of rail IBCs, a blind IBC type recognition based on force sensor and close-range proximity sensors, and other protection gears enabling the manipulator to work in harsh outdoor working environments.

The invention relates to the technical field of financial bill management, and discloses a financial bill automatic identification generation and decision-making method and system, and the method comprises the steps: firstly receiving an original bill image, carrying out the preprocessing of the original bill image, carrying out the format analysis and classification of the enhanced image through a computer vision technology, and distinguishing a known standard format from an unknown format. For a known format, accurately extracting a key region text block by applying an OCR module based on template positioning; and for an unknown format, a general document understanding model is adopted to obtain a preliminary key information key value pair. And then, the extracted information is converted into structured data through a key information structured extraction module, and the structured data is verified by a data verification and business rule engine. If the verification is passed, structured bill information is output; otherwise, sending to a manual intervention queue for further auditing. According to the method, the efficiency and accuracy of financial bill automatic processing are effectively improved, and meanwhile, the flexibility of the system for adapting to different bill formats is enhanced.

The invention relates to the technical field of surveying and mapping information processing, and discloses a surveying and mapping information intelligent analysis and visualization system based on the Internet of Things. According to the system, a building space data acquisition terminal acquires geometric feature point cloud and environmental parameters of the surface of a building structure in real time through distributed Internet of Things nodes; the multi-source heterogeneous data fusion engine performs space-time alignment processing on the geometric feature point cloud to generate a building total-factor topological skeleton with an absolute coordinate system; the three-dimensional topological relation reconstruction module is used for extracting a spatial constraint relation of building components according to the topological skeleton and establishing a hierarchical building information model capable of being edited in a parameterized manner; and the dynamic visual rendering platform is used for generating a multi-scale spatial index based on the hierarchical building information model, and driving real-time light and shadow effects and interactive sectioning analysis. According to the system, full-process automatic processing and dynamic visualization of building surveying and mapping data are realized.

The invention discloses a multi-modal data automatic processing and information extraction method, and belongs to the technical field of data processing. Comprising the steps of establishing an original knowledge base according to original training data in a business scene; preprocessing the original multi-modal data in the original knowledge base to obtain a preprocessed knowledge base; inputting the preprocessing knowledge base into a knowledge retrieval unit; a text to be queried is converted into a query vector, the distance between the query vector and a knowledge fusion vector representation vector in the knowledge retrieval unit is calculated, and a retrieval result is obtained through an approximate nearest neighbor retrieval algorithm; and performing multi-modal data fusion on a retrieval result through a cross-modal Transform model, and combining fused semantics with user query to generate an answer. According to the method, data of multiple modes such as texts, images, audios and videos can be processed, multi-mode fusion and reasoning are carried out through the visual language model, accurate extraction and structured storage of information are achieved, and the efficiency and quality of data analysis and mining are improved.

The invention provides a non-technician-oriented script intelligent adaptation and visual arrangement method and a non-technician-oriented script intelligent adaptation and visual arrangement system. The method comprises the following steps: acquiring a script file uploaded by a user, extracting a dependency library through an AST analysis technology, and constructing an isolation container environment; performing intelligent identification and conversion on a file path and database connection in the script to generate a standardized API call; carrying out input and output analysis on the basis of the converted script, and carrying out DAG workflow arrangement in a visual mode; performing function-level packaging and standardization processing on the script component in the workflow to realize component multiplexing and version management; and finally, configuring a scheduling strategy and carrying out automatic operation monitoring. According to the method, a script environment depends on automatic processing and intelligent path adaptation, and visual arrangement and modular multiplexing are combined, so that non-technical personnel can independently complete the whole process from AI script generation to a production-level automatic process, the problem of'last kilometer 'in script deployment is solved, and the working efficiency is improved.

The invention discloses a cross-border e-commerce anti-counterfeiting tracing method and system based on a block chain, and belongs to the technical field of computer application. The method comprises the steps of obtaining full-link information of commodity production, storage, logistics and sales links, performing encryption processing through a composite hash function, storing the information to a block chain by using an improved consensus mechanism, constructing an intelligent contract to realize automatic processing of commodity state changes, and scanning a code by a consumer to compare a hash value to verify authenticity. The system comprises an information acquisition module, a hash encryption module, a consensus storage module, an intelligent contract module and a verification module. According to the scheme, it is guaranteed that data cannot be tampered through the composite hash function, the consensus efficiency is improved through the hierarchical verification structure and the dynamic node weight, state monitoring and automatic claim settlement are achieved with the help of the intelligent contract, the problems of data fragmentation, difficult anti-counterfeiting, poor supervision cooperation and the like in cross-border e-commerce are solved, full-link credible evidence storage and automatic supervision are achieved, and the safety of cross-border e-commerce is improved. And the cross-border commodity anti-counterfeiting and traceability efficiency is improved.

The invention discloses a personalized digital human image creation and generation system based on deep learning, which relates to the technical field of digital human generation and comprises a multivariate data acquisition module, an image creation module, a model storage module, a matching module and a rendering interaction module. The multivariate data acquisition module collects facial images and whole body photos through a camera, and records voice samples through a microphone. According to the invention, by constructing the multivariate data acquisition module, the image creation module, the model storage module, the matching module and the rendering interaction module, full-process automatic processing from data acquisition to digital human image generation is realized; the multivariate data acquisition module can comprehensively capture the appearance and voice features of a user, and the image creation module extracts feature vectors by using a deep learning technology and generates a personalized digital human image by using a generative adversarial network technology.

The invention relates to the technical field of PCB detection, and discloses an online defect detection method and system in the PCB production process and computer equipment, the detection accuracy can be improved by combining production parameters, image information and a design circuit diagram, potential defects can be found in the early stage, the PCB is divided into a plurality of areas, and the detection efficiency is improved. According to the PCB, each area can be independently welded and detected, the complexity of the whole PCB is reduced, the PCB is divided into a plurality of areas which are detected one by one, a specific defect area can be effectively positioned, through the regionalized detection and maintenance process, the unqualified area can be locally processed, the production efficiency is improved, and the production cost is reduced. By adopting the strategy based on multi-round detection, feedback and regional repair, through accurate positioning, local repair, detection efficiency improvement and automatic processing, the rejection rate of unqualified products is greatly reduced, the maintenance success rate is improved, and the problems of difficulty in PCB defect detection and resource waste in the prior art can be effectively solved.

The invention discloses a multi-agent-based automatic processing system and a PLC automatic programming system, and belongs to the technical field of artificial intelligence. The system comprises a distribution agent and a plurality of working agents, the distribution agent is used for acquiring a question input by a user, analyzing the question to determine a target working agent suitable for solving the question, and routing the question to the target working agent; and the working agent is used for answering the received questions to obtain answers corresponding to the questions and returning the answers to the distribution agent. According to the method, the multi-agent framework for managing the large model is built, the distribution function and the work function of the agents are separated, modularization of the system is achieved, the system can flexibly meet various application requirements, large-scale modification does not need to be conducted on the whole process, the customization and maintenance cost of the requirements is reduced, and the implementation efficiency of the system is improved. And the processing efficiency of the automation process is improved.

The invention relates to the technical field of data security, in particular to an unstructured video data automatic classification method, which comprises the following steps: S1, video data preprocessing: standardizing video data to a uniform format and size, and carrying out noise processing; s2, video data feature extraction and multi-mode feature fusion: feature extraction is performed on the preprocessed video data from three modes of audio, video and text, time sequence processing is performed, and multi-mode feature fusion is performed; s3, video data same-category matching: classifying the fused multi-modal features to complete video classification; according to the invention, multi-modal information in a video can be captured more accurately, and automatic processing of video data is realized; high processing efficiency and classification accuracy are kept in large-scale data, meanwhile, the degree of automation is improved, the necessity of manual participation is reduced, and the overall process is optimized.

The invention discloses a hydraulic engineering dam body crack detection method and system based on machine vision, and relates to the technical field of computer vision. A high-definition camera is used for shooting a dam body image, obtaining a sample data set, extracting feature parameters of different noise types, and constructing a feature database; filtering the current dam body image to obtain a first dam body image, enhancing the crack gray scale difference of the first dam body image, obtaining a second dam body image, segmenting the second dam body image, screening candidate cracks in the crack image, and identifying real cracks according to the edge features of the candidate cracks. According to the method, a feature database is constructed, a targeted dam body image processing flow is combined, a high-definition camera collection and automatic processing flow is used, filtering parameters are dynamically adjusted by constructing the feature database, gray level enhancement and precise segmentation are combined, real cracks are precisely recognized through edge feature analysis and comparison, and quantitative parameters are output; and a reliable basis is provided for dam body safety assessment.

The invention relates to a large model business logic processing method and system based on workflow engine and domain knowledge fusion, and is suitable for automatic processing of complex multi-node and multi-branch business processes. According to the method, natural language input of a user is analyzed through a large language model, a service intention is recognized, and the service intention is converted into an executable task process through a workflow engine. And the workflow engine dynamically adjusts an execution path according to rules and data in the domain knowledge graph to realize efficient parallel processing of tasks. The system integrates a workflow engine, a domain knowledge graph and a large language model, supports real-time data processing, rule matching, conflict resolution and decision optimization, is suitable for the fields of water conservancy, medical treatment, finance and the like, automatically generates and executes a complex business process, and optimizes a decision process. The system improves the accuracy and execution efficiency of business decision through deep fusion of domain knowledge.

The invention discloses welding and grinding integrated machining equipment for a charging pile in the field of charging pile machining equipment. The welding and grinding integrated machining equipment comprises a rotating disc device and a machining device. The rotating disc device comprises a rotating disc and a plurality of positioning jigs. And the plurality of positioning jigs are uniformly distributed in the circumferential direction of the rotating disc. And the positioning jig is rotationally connected with the rotating disc. The rotating disc is provided with a rotating driving component used for driving the positioning jig to rotate. The machining device comprises a welding mechanism and a polishing mechanism. The welding mechanism and the polishing mechanism are arranged on the sides of the two positioning jigs correspondingly. The welding mechanism comprises a laser welding head and a welding feeding component used for driving the laser welding head to move. The grinding mechanism comprises a grinding component and a grinding feeding component used for driving the grinding component to move. According to the welding and grinding integrated machining equipment for the charging pile, automatic machining of annular welding and grinding treatment on a charging pile product can be achieved, the stability is high, repeated positioning of the charging pile product is avoided, and the production efficiency is high.

The invention discloses an SAR (Synthetic Aperture Radar) soil surface water content inversion method and device based on deep learning, and the method comprises the steps: constructing a deep learning regression model for predicting the volume content of soil water through combining SAR data, auxiliary data and in-situ sensor data; a ConvNeXt model is adopted to construct a parallel convolution encoder to solve multi-source data with different input resolutions, and back scattering coefficients, spectral information, digital elevation model high-resolution data and soil sand content, sludge content, clay content and stacking density low-resolution data are fused into soil moisture estimation. And the inference capability of unknown data is improved. The model obtained by training can realize large-range and high-resolution automatic estimation of the water content of the soil surface layer. According to the invention, the influence of radiation transmission noise is avoided, the inversion precision of a vegetation coverage area is improved, and large-range high-resolution automatic processing of soil humidity products is realized.

The invention relates to the technical field of equipment abnormity control, and discloses an equipment abnormity self-closed-loop control system. An anomaly detection engine of the system collects operation state data of target equipment in real time, and performs preliminary anomaly marking according to a preset anomaly judgment rule; the dynamic analysis unit receives the preliminary anomaly marks, generates anomaly feature vectors in combination with historical operation data, and inputs the anomaly feature vectors into a multi-dimensional evaluation model to divide anomaly levels; a strategy generator is matched with a preset repair strategy library according to the abnormal grade division result, and a corresponding repair instruction sequence is generated; the execution control module analyzes the repair instruction sequence, and dispatches hardware resources to execute repair operation according to a preset execution priority; and the feedback verification unit collects the running state data again after restoration, and compares the running state data with the initial abnormal mark to generate a restoration verification result. The system realizes full-process automatic processing of equipment exceptions, and improves exception processing efficiency and equipment operation stability.

The invention discloses an automatic processing method and system for grid-connected test data of a photovoltaic inverter. The method comprises the following steps: acquiring original data of a grid-connected test of the photovoltaic inverter; acquiring configured parameters, variables and conversion functions; original parameters and test values are extracted from the original data based on the target parameters, then conversion data are obtained based on the conversion function and variable conversion processing, and the conversion data are stored; obtaining configured stage interval division parameters, stage interval division variables and stage interval division functions; according to the stage interval division parameter, the stage interval division function and the stage interval division variable, the operation of dividing the conversion data into a plurality of stage intervals is executed, and each divided stage interval comprises the stage interval division parameter, a starting row, an ending row, and numerical values corresponding to the starting row and the ending row corresponding to the stage interval division parameter; and generating an analysis report. According to the method, the analysis report generation efficiency and accuracy are remarkably improved, human errors are reduced, and the time of testers is saved.

The invention provides an infrared thermal imaging image processing method for a pain area, and relates to the field of image enhancement, and the method combines multi-scale adaptive contrast enhancement and a bidirectional circulation mechanism, captures global and local temperature features of an infrared image, constructs an iterative feature enhancement module through an incremental fusion strategy, and carries out the image enhancement through the iterative feature enhancement module. Different level features are fused in stages, learnable parameters are introduced to dynamically adjust the new and old feature fusion proportion, the adaptability and flexibility of the model are improved, and a staged training strategy is adopted, so that the model can learn low-level thermal image information and also can extract high-level structures and thermal anomaly semantic features. According to the method, the adaptability of the model to different types of focus areas is enhanced, and the actual demand of efficient and automatic processing of the infrared image is met.