85 results about "Information synthesis" patented technology

In a described embodiment, a multi-agent system for processing information is provided including a data processing agent configured to ingest and normalize raw data inputs to produce standardized data and a standards integration agent configured to apply reporting standards into the standardized data thereby generating integrated reporting standards. The system further includes a performance alignment agent configured to align performance indicators based on the standardized data and the integrated reporting standards and an information synthesis agent configured to process narrative information from the standardized data and the integrated reporting standards. An orchestration framework configured to manage operations of the data processing agent, the standards integration agent, and the performance alignment agent to produce a regulatory repot compliant with regulatory requirements is further provided. The orchestration framework is further executable by a large language model.

The invention discloses an industrial visual detection system based on multi-modal fusion, which belongs to the technical field of industrial data acquisition, processing and processing, and comprises a multi-modal data acquisition and calibration module, a scene image capture module, a visual information synthesis module, an algorithm optimization and training module and a multi-modal image output module, the multiple modules are integrated into the industrial visual detection system for multi-modal data acquisition, processing and fusion, high-quality original data are provided for subsequent image analysis, images of industrial scenes can be automatically captured under different illumination conditions, an original image database containing various illumination and scene conditions is constructed, and the visual detection system has the advantages of being simple in structure, convenient to operate and high in practicability. The system can operate stably, high-precision analysis and processing of the image data set in the industrial scene are realized, the corresponding fusion image is generated, the industrial visual inspection report is generated based on the fusion image, and the adaptability and reliability of the industrial visual inspection system are improved.

The invention provides a low-light image enhancement method and device based on infrared visible light information integration, and belongs to the technical field of image enhancement, and the method comprises the steps: carrying out the processing of a normal illumination image through a series of image degradation methods based on image augmentation, and obtaining a pseudo low-light image needed by training; enabling the pseudo low-light image and the corresponding infrared image to pass through a submerged space and a multi-layer encoder to obtain a deep multi-scale feature, and building a multi-modal information interaction module based on sparse cross attention to process a dual-modal variable-scale feature and enhance feature interaction fusion; and a dual-mode residual feature enhancement diffusion model is established, and the feature enhancement diffusion model comprises a feature splicing module and a series of multi-mode information interaction modules, so that complementary features are learned and fused in the denoising process, the features are mapped to a normal exposure domain, and deep integration of image information is realized. According to the method, low-light images under various exposure conditions can be effectively enhanced, and the robustness is high.

The invention discloses a transparent object six-degree-of-freedom grabbing method based on RGB-D multi-mode information fusion, and mainly relates to the technical field of computer vision and robot grabbing. An RGB-D camera is used for shooting an RGB image and a depth image of a transparent object, after the depth image is corrected through a depth completion network, RGB two-dimensional image information and depth information are synthesized into a point cloud, the pose of the clamping jaw for grabbing the transparent object is obtained through a 6D grabbing pose estimation algorithm, and the clamping jaw is deployed on a real object mechanical arm for grabbing; according to the invention, the perception capability of the system to the transparent object is obviously improved, the problem that the depth acquisition effect of the existing RGB-D sensor to the transparent object is poor is solved, six-degree-of-freedom flexible grabbing is realized, and the adaptability and robustness of the system in processing various transparent objects are improved.

The invention relates to the technical field of natural language processing, in particular to a verifiable large model retrieval enhancement generation system and method based on an evidence chain, and the method comprises the steps: receiving an initial query, recognizing the fuzziness and information gap of the initial query in combination with an associated retrieval document, and generating a supplementary query set; based on the initial query, the supplementary query and the corresponding retrieval document, generating candidate answers with references and verifying the information supportability of the candidate answers; for the candidate answers passing the verification, extracting support information and constructing a hierarchical attribution mapping relation; and integrating the information to form to-be-evaluated information, and if the current verified to-be-evaluated information meets a preset sufficiency condition, integrating the generated preliminary answer and the to-be-evaluated information to synthesize a target answer. The method effectively overcomes the defects that a traditional RAG system is fragmented in information integration, has one-sided fuzzy query and answer, is low in attribution efficiency and excessively depends on retrieval content, and has the advantages of answer comprehensiveness, verifiability and deployment lightweighting.

A data communication network includes a data communication node, an imaging device, and an information handling system. The data communication node establishes a data connection with a user equipment device. The imaging device provides image information for a coverage area associated with the data communication node. The information handling system is coupled to the data communication node and to the imaging device. The information handling system receives the image information, synthesizes a 3D map of the coverage area based upon the image information, receives first coverage information from the first data communication node, correlates the first coverage information with the 3D map to generate a coverage map of the coverage area, to generate a first connectivity pattern associating a quality of connectivity provided by the first data communication node within the coverage area, and determines a first location of the first user equipment device within the connectivity pattern based on the image information.

A feed raw material nutritional value data synthesis method based on a large language model comprises the following steps: step 1, sorting and collecting data, and constructing a question and answer text data set, a professional vocabulary annotation data set and an instruction fine tuning data set; 2, selecting a lightweight open-source large language model for fine tuning by using a question and answer text data set, a professional vocabulary annotation data set and an instruction fine tuning data set; 3, the training model is used for extracting data, an RMSE function is used as a loss function of numerical data, and a cross entropy loss function is used as a loss function of text data for model training; 4, constructing a raw material nutritional value data set; and 5, generating corresponding raw material nutritive value data by the large language model, and performing back propagation on the model. The method overcomes the defect that natural language information and real information are difficult to use during synthesis of the nutritive value data of the feed raw materials, and solves the problem that the feed industry is lack of an information synthesis method.

The invention discloses a student comprehensive evaluation method and device, a storage medium and electronic equipment. The method comprises the following steps: converting student information data in a student information database through a student information reader to obtain a data text fragment; synthesizing the data text fragments into an electronic document based on a student information synthesizer; converting the electronic document into a large model cue word through an evaluation cue word generator and an evaluation template library; and calling the large language model, and converting the large model cue word into a student evaluation report according to the large language model. Through the method and the device, the problem that comprehensive evaluation on students is not comprehensive based on student information data in the related technology is solved.

The invention discloses a halftone image reversible information hiding and extracting method and device and a medium, and relates to the field of image encryption, and the method comprises the steps: obtaining an original halftone image and original secret information; using a Hash algorithm to calculate summary information of the original halftone image; synthesizing the summary information with the original secret information to form to-be-hidden secret information, and storing the to-be-hidden secret information as a secret image; encrypting the original halftone image by using a ZUC encryption algorithm to obtain an encrypted halftone image; according to the encrypted halftone image, using a polynomial secret sharing algorithm to obtain N shared original images; according to the secret image, utilizing a polynomial secret sharing algorithm to obtain N shared secret images; and synthesizing the N shared original images and the N shared secret images to obtain N secret-carrying shared images. According to the method, the applicability, the confidentiality and the correctness of halftone image sharing are improved.

In described embodiments, there is provided a multi-agent system for processing information, comprising a data processing agent configured to ingest and standardize raw data input to produce standardized data, and a standard integration agent configured to integrate the standardized data with the standard integration agent. The standard integration agent is configured to apply a reporting standard to the standardized data to generate an integrated reporting standard. The system also includes a performance alignment agent configured to align performance metrics based on the standardized data and the integrated reporting criteria, and an information synthesis agent configured to process narrative information from the standardized data and the integrated reporting criteria. An orchestration framework is also provided that is configured to manage operation of the data processing agent, the standard integration agent, and the performance alignment agent to generate regulatory reports that comply with regulatory requirements. The orchestration framework may also be executed by a large language model.

The invention discloses a voice recognition information display method and device and electronic equipment, and belongs to the technical field of terminals. The method comprises the following steps: under the condition that a first environment audio collected by a microphone comprises a wake-up keyword, performing voice recognition on a synthesized environment audio to obtain voice recognition original information; the synthesized environment audio is obtained by splicing a second environment audio, a first environment audio and a third environment audio, the second environment audio is cached environment audio, and the second environment audio is environment audio collected in a cache duration before a first timestamp; the first timestamp is a wake-up start timestamp of the wake-up keyword; the third environment audio is the environment audio collected after the second timestamp; the second timestamp is a wake-up ending timestamp of the wake-up keyword; voice recognition information is displayed, the voice recognition information comprises at least part of information in the voice recognition original information, and the voice recognition information comprises the wake-up keyword and character information forming complete semantics with the wake-up keyword.

The invention discloses a biological data anomaly detection method based on semantic information fusion, and relates to the technical field of computer processing, and the method comprises the following steps: S01, constructing biological entity nodes and relation edges through a depth map neural network, generating an adjacency matrix and a node attribute matrix, aggregating node neighbor information by using a message passing mechanism, and generating a node attribute matrix; a biological network architecture model is obtained; s02, constructing a semantic fusion space based on a large model, analyzing deep semantic information and node association information of nodes, and synthesizing a few abnormal node candidate sets; and S03, adding the composite node candidate sets into the original data set one by one through an edge generator, and inputting the composite node candidate sets into a reinforcement learning module for screening. According to the method, classification and risk assessment of biological data are optimized by utilizing large-model semantic analysis and biological network construction, so that abnormal biological data can be quickly identified through multi-source data fusion and deep learning analysis in the early stage of virus transmission, and accurate detection and intelligent early warning are realized.

This invention discloses a Wi-Fi visualization perception method based on Markov transition fields, primarily addressing the existing issues of poor channel state information (CSI) feature extraction and low recognition accuracy. Its implementation involves: utilizing Markov state transition characteristics to characterize the temporal variations of Wi-Fi signals and transforming CSI data into CSI images; adaptively correcting the CSI images based on a channel attention mechanism to focus on the channel feature information of the CSI images and synthesize RGB three-channel CSI images; dividing the CSI images into training and test sets according to a set ratio; constructing a Visual Transformer (ViT) network model and training it using the training set; and inputting the test set into the trained ViT network model to obtain gesture recognition results. This invention can effectively extract channel features from CSI images, improve the accuracy of indoor human gesture recognition, and can be used for visualizing and recognizing dynamic human gestures indoors.

This invention discloses a secure voice-based intelligent customer service system and interaction method based on a multi-agent architecture. The system includes an ASR (Automatic Speech Recognition) module, multi-layered security barriers, a main retrieval agent, a specialized retrieval agent cluster, a parallel retrieval and result aggregation module, an LLM (Limited Language Modeling) synthesis engine, and a TTS (Text-to-Speech) module. Through multi-agent system architecture and methodological design, this invention achieves modular processing, parallel retrieval tasks, and closed-loop security control. By enabling independent calls between input, output, agents, and inference stages via multi-layered security barriers, the system effectively mitigates risks such as prompt word injection, indirect injection attacks, harmful content generation, and information leakage. Sensitive information identification, access permission verification, and content compliance review are embedded in each stage of input, retrieval, information synthesis, and output to prevent sensitive data leakage and meet the application requirements of high-security business scenarios (such as finance, telecommunications, and government services).

This invention provides a multi-sensor information fusion method and apparatus for multi-target recognition scenarios, relating to the field of intelligent sensing technology. The method includes: acquiring multi-sensor point cloud data for each target to be identified through a sensor system; performing polarization slicing on the multi-sensor point cloud data to obtain corresponding multi-path information slices; performing spatiotemporal synthetic polarization coding on the multi-path information slices to obtain a synthetic coding stream formed by multiple polarization codes; and calling a spatiotemporal neural network model to extract multi-scale semantic information of the target to be identified from the synthetic coding stream for alignment evaluation of each target. This invention addresses the shortcomings of existing multi-sensor systems in multi-target recognition scenarios, such as low information coding efficiency, prolonged data processing time, and severe information synthesis distortion.

The invention relates to an information synthesis system comprising: - at least one information receiving means (R1, R2) for receiving text (T), audio (A) and / or video (V) files; - a means (C) for converting a multimedia file (A, V) into text in order to obtain at least one converted file (FC); - a first artificial intelligence (AI) model for analyzing the text file (T) and / or the converted file (FC), and for generating a mental map (CM) on the basis thereof, the first artificial intelligence (AI) model being constructed by machine learning from construction data comprising reference files (T1, T2, …, Ti, A1, A2, …, Ai, V1, V2, …, Vi), as well as corresponding reference mental maps (CM1, CM2, … CMi); the invention further relates to a method and a computer program based on such a system.

The application relates to the technical field of natural language processing, in particular to an evidence chain-based verifiable large model retrieval enhancement generation system and method, which comprises the following steps: receiving an initial query, identifying the ambiguity and information gap of the initial query in combination with associated retrieval documents, and generating a supplementary query set; generating a cited candidate answer based on the initial query, the supplementary query and the corresponding retrieval document, and verifying the information supportability of the cited candidate answer; extracting supportable information from the verified candidate answer and constructing a hierarchical attribution mapping relationship; integrating the above information to form to-be-evaluated information; if the to-be-evaluated information currently verified satisfies a preset sufficiency condition, integrating a generated preliminary answer and the to-be-evaluated information to synthesize a target answer. The application effectively solves the defects of the traditional RAG system, such as information integration fragmentation, one-sided query answering, inefficient attribution and excessive dependence on retrieval content, and has the advantages of comprehensive answer, verifiability and lightweight deployment.

A method for synthesizing feed raw material nutritional value data based on a large language model, comprising the following steps: Step 1: collating and collecting data, constructing a question-answering text data set, a professional vocabulary annotation data set, and an instruction fine-tuning data set; Step 2: using the question-answering text data set, the professional vocabulary annotation data set, and the instruction fine-tuning data set to select a lightweight open source large language model for fine-tuning; Step 3: training a model for extracting data, using the RMSE function as the loss function for numerical data, and using the cross entropy loss function as the loss function for text data for model training; Step 4: constructing a raw material nutritional value data set; Step 5: the large language model generates the corresponding raw material nutritional value data, and the model is back-propagated. The present invention overcomes the shortcomings of being difficult to use natural language information and difficult to use real information when synthesizing feed raw material nutritional value data, and solves the pain point of the lack of information synthesis methods in the feed industry.

The invention provides a multi-sensor information fusion method and device for a multi-target recognition scene, and relates to the technical field of intelligent perception, and the method comprises the steps: obtaining multi-sensor point cloud data of each to-be-recognized target through a sensor system, and carrying out the polarization slicing of the multi-sensor point cloud data, and obtaining a corresponding multi-path information slice; performing space-time synthesis polarization coding on the multi-channel information slices to obtain a synthesis coding stream formed by multivariate polarization codes; and calling a space-time neural network model to extract multi-scale semantic information of the to-be-identified targets from the synthesized coding stream, wherein the multi-scale semantic information is used for performing alignment evaluation on each to-be-identified target. The method is used for overcoming the defects that in the prior art, a multi-sensor system in a multi-target recognition scene is low in information coding efficiency, long in data processing time delay and serious in information synthesis distortion.

The present invention provides, for example, a novel mechanism that can minimize the user burden for coordinating an LMS and an image forming apparatus. [Solution] The image forming apparatus comprises: an acquisition unit that acquires the cooperation status between a learning management device and a predetermined image forming apparatus; a first determination unit that determines whether or not there is a predetermined image forming apparatus that is not cooperated with the learning management device using the cooperation status; a synthesis unit that, if the first determination unit determines that there is a predetermined image forming apparatus that is not cooperated, synthesizes identification information that can identify the number of inputters who input information into the managed sheet into the data for forming the managed sheet; and an output unit that outputs an image using the data.

Embodiments of the present application disclose an information processing method and device. The method comprises: extracting key text information for multimedia data from description text information; obtaining data attribute information of the multimedia data, and selecting a target cover template for the multimedia data from a cover template set according to the data attribute information; obtaining first cover information of the multimedia data, and performing information synthesis on the key text information and the first cover information according to the target cover template to obtain second cover information of the multimedia data. By using the embodiments of the present application, the content of the second cover information of the multimedia data can be enriched, and the relevance between the content of the second cover information and the content of the multimedia data can be improved. The method disclosed in the present application can also be applied to the field of natural language processing technology, for example, the key text information is extracted from the description text information by using the natural language processing technology.

The application relates to the technical field of data processing. In particular, the application relates to an information processing method, device and medium. The method comprises the following steps: in response to an access request about target information sent by a corresponding first user equipment, obtaining one or more first target identification information and second target identification information according to target identity information; for each target encryption block, sending an acquisition request about the target encryption block to a corresponding target storage node; receiving one or more target encryption blocks sent by one or more target storage nodes; and sending the one or more target encryption blocks to the first user equipment, so that the first user equipment uses a first private key corresponding to a first public key to decrypt each target encryption block, and performs information synthesis on the decrypted one or more target encryption blocks according to an information synthesis rule. Through the fragmentation and distributed storage mode, information security is realized, and the purpose of fine control of the information viewing range is achieved.

The invention relates to the technical field of electric power measurement, and discloses a carbon emission measurement anomaly detection method and system based on artificial intelligence, and the method comprises the steps: carrying out the standardization preprocessing of carbon emission time series data, and generating a query matrix Q, a key matrix K and a value matrix V; q and K are input into a dynamic frequency module with three parallel branches, multi-scale frequency features are extracted through dynamic convolution and FFT transformation of different scales, and the features are stored and reconstructed by using a memory matrix; after feature correlation is calculated and converted back to a time domain, time delay operation is performed on V, and dynamic information synthesis is performed; and reconstructing the synthetic features through an encoder-decoder architecture, and judging an abnormal state based on a reconstruction error. According to the method, the frequency domain and time domain characteristics of the data are effectively captured, excessive generalization is inhibited, and accurate carbon emission metering anomaly detection is realized.

The present invention belongs to the field of seismic engineering drawing, and discloses a method for batch generating result data drawing library files. First, the field acquisition parameter list and processing parameter list are extracted from the field report file and the seismic line CMP coordinate - elevation file, and saved in the LTP and LSL library files, and the standard templates of the LTP and LSL library files are established; the field report files and seismic line CMP coordinate - elevation files of each seismic line are collected and named in a unified format; the information extracted from the seismic line CMP coordinate - elevation file and the field report file is synthesized to obtain the total drawing parameter information table, and the total drawing parameter information table is batch written into the standard drawing library files according to the established standard templates of the LTP and LSL library files. The present invention is applicable to batch generating result data drawing library files. By batch writing the total drawing parameter information table into the standard drawing library files according to the established standard templates of the LTP and LSL library files, the production efficiency is improved and the workload of processing personnel is reduced.

The invention relates to a multi-interface mobile application evaluation method and device based on a multi-modal model, and belongs to the field of mobile application quality testing. The method comprises the steps of test item collection, information extraction, review information synthesis, information analysis and result filtering and output, specifically, test link collection is completed through a graphical user interface proxy technology, accurate information extraction is completed based on a multi-modal large language model and tool calling, and the result is output. User demand analysis and review task planning are completed through multi-agent cooperation, deep consistency analysis is completed based on thinking chain reasoning, and finally a high-quality problem report is output through an intelligent filtering mechanism. According to the method, automatic extraction, intelligent analysis and systematic evaluation of cross-page information are realized, the problem of information inconsistency in the mobile application can be efficiently identified, the pertinence and effectiveness of problem discovery are improved, the high confidence of a test result is ensured, the manual review pressure is relieved, and technical support is provided for application quality optimization.

The present application relates to the technical field of image data transmission, in particular to a kind of intelligent laser obstacle clearing instrument remote monitoring system, laser radar depth and pixel data are collected and generate obstacle space positioning set, according to depth difference generation monitoring picture partition mark chart, set difference compression ratio and generate partition encoding transmission package, monitor transmission performance and correct generation encoding data package, fusion obstacle information synthesis remote monitoring picture data package.The present application, fusion laser radar, depth sensor and camera data, generate obstacle space positioning set under unified coordinate, realize the accurate acquisition of position and form, divide area by depth difference, detail area low compression ratio coding, ordinary area high compression ratio coding, reduce redundant transmission and improve efficiency, combined with link real-time adjustment to cope with delay packet loss and distortion, ensure image stability and quality, in remote monitoring fusion obstacle information and image, realize state accurate display, improve system responsiveness and reliability.

The embodiment of the invention provides a data processing method, electronic equipment, a computer readable storage medium and a computer program product, and the method comprises the steps: obtaining original signaling of each reference point in a network system; determining an original internet log of each reference point according to the original signaling; and under the condition that the original internet surfing log does not comprise the network type label, performing associated information synthesis processing on the original internet surfing log to obtain a target internet surfing log. According to the technical scheme, the increasingly refined online log monitoring requirement can be well met.

The invention discloses a YOLOv5s-based multi-modal feature fusion apple recognition method. The method comprises the following steps of (1) image acquisition; (2) decomposing and reconstructing a color image; (3) carrying out image processing on the edge features; (4) obtaining a key fruit feature map; (5) obtaining point cloud coordinate information; (6) multi-modal feature fusion: synthesizing R, G, B, the key fruit feature map, the depth image and the point cloud coordinate information XYZ into an eight-channel image; (7) carrying out channel number modification on an input layer of the YOLOv5s; (8) taking the fused multi-modal features as input, and carrying out deep learning training; and (9) verifying and evaluating the trained model by using the new data set. According to the method, on the basis of a conventional YOLOv5s model, fruit feature channels in various forms such as RGB images, key fruit features, depth information and point cloud coordinate information are fused at the input end, so that the apple detection precision is effectively improved, and the result is subjected to three-dimensional point cloud visualization.

An information processing system according to the present disclosure comprises: a reception unit that receives, from a user, subjective evaluation information relating to speech evaluation, and designation of a speaking style; a generation unit that, on the basis of the subjective evaluation information and the designation of the speaking style, converts a low-dimensional embedding vector corresponding to the speaking style adjusted by the user to generate a high-dimensional speaking style embedding vector; and a speech synthesis unit that synthesizes speech from the speaking style embedding vector and text information defining speech to be synthesized.