196results about How to "Efficient retrieval" patented technology

The invention relates to the technical field of image processing, and discloses an industrial article appearance detection method and system based on machine vision. The method comprises the steps that a workpiece image is collected, and a standardized image is obtained through Gaussian filtering, histogram equalization and Otsu algorithm preprocessing; feature vectors are extracted through edge detection, Hough transform and a gray-level co-occurrence matrix; training a defect identification model by adopting a CNN of an attention mechanism; inputting an image for real-time detection; fusing the detection data and the environmental parameters by using a D-S theory; and establishing a database based on a distributed architecture to generate a quality report. According to the method, the detection accuracy is improved through multi-source information fusion, and efficient management and analysis of mass detection data are realized by adopting a distributed architecture.

The invention provides a security management and retrieval method based on Internet of Vehicles data, and the method comprises the steps: carrying out the cooperative training of a global key management model through a federated learning technology on the premise of not leaking the original data of all parties, and achieving a security key management scheme under the participation of multiple parties through a model parameter aggregation and updating mechanism; when data retrieval is needed, a user submits a retrieval request and identity authentication information, and after a system verifies the identity of the user, a ciphertext data identifier meeting conditions is matched in an attribute index according to a keyword and an authorization attribute of the request; the system acquires corresponding ciphertext data from a distributed database according to the ciphertext data identifier, and directly performs keyword matching calculation on the ciphertext data through a secure multi-party computing protocol under the condition of not decrypting the data; and according to the mined security threats and abnormal modes, a data encryption strategy and an access control strategy are dynamically adjusted, authority limitation or access blocking is performed on suspicious users, and the security protection capability of the system is improved.

The invention relates to the technical field of data storage management, in particular to a data storage method based on a large model. The method comprises the following steps: performing input class cluster fragmentation optimization on a target pre-training large model to obtain storage modulus fragmentation data; constructing an intelligent fragmentation storage strategy by using the storage modulus fragmentation data; obtaining target model training data; performing intelligent fragmentation storage on the target model training data by using an intelligent fragmentation storage strategy, and performing redundancy compression optimization to obtain dynamic redundancy storage index data; and training data storage space optimization is carried out according to the dynamic redundancy storage index data, and an optimized data storage strategy is obtained. According to the method, intelligent fragmentation storage and refined data redundancy compression are performed on the data, so that efficient and stable model training data access is realized, the problem of low data storage and access efficiency in a large model training process is solved, and the model training efficiency and reasoning real-time performance are remarkably improved.

The invention discloses a cross-modal image text retrieval method based on deep learning, and provides a novel cross-modal feature extraction and alignment framework, efficient cross-modal retrieval is performed by learning semantic representation of an image and a text in a common feature space, the framework comprises a plurality of modules, and in a feature extraction stage, the cross-modal feature extraction and alignment framework is used for extracting and aligning the images and the texts. BERT Tokenizer and BERT Embedding are adopted for text coding, and the image feature extraction is combined with a Faster R-CNN (Convolutional Neural Network) model and a ResNet-101 model, so that the dimensional consistency of image features and text features is ensured. In the feature alignment stage, fine-grained semantic alignment of image and text features is realized through an I2T Attention module and a T2I Attention module, and the cross-modal matching precision is remarkably improved. In the correlation scoring stage, a correlation scoring matrix is generated by calculating the similarity score between the image features and the text features, so that the accuracy of cross-modal matching is improved. And further optimizing the feature alignment effect through normalization and attention redistribution. In an optimization stage, the system innovatively adopts a shared semantic and sorting loss strategy, integrates an OpenCLIP model framework, efficiently mines a semantic relationship between an image and a text from unlabeled large-scale data through comparative learning, and shows strong transfer learning ability and inference precision.

The invention belongs to the field of database enhancement, and particularly relates to an automatic RAG knowledge base construction method and system.The method comprises the steps that firstly, an RAG knowledge base is constructed, a user can customize an icon and a name of the RAG knowledge base, meanwhile, a data embedding model and a parallel retrieval mode function module are built in, and a text recall test tool is configured; the data embedding model can convert unstructured data into vectors and store the vectors in the classification vector database; a to-be-retrieved document is uploaded to a knowledge base to be preprocessed, a document text demand space is obtained, an optimal effective recall information fragment set is obtained from parallel retrieval modes of vector retrieval, keyword retrieval, mixed retrieval and the like of the knowledge base by utilizing a segmented TopK recall strategy and a text recall test tool, and the optimal effective recall information fragment set is stored in a database; and finally, obtaining an effective question and answer result according to the document text demand space and the optimal effective recall information fragment set, thereby improving the construction efficiency of the knowledge base and the question and answer accuracy.

The invention discloses an enterprise micro-marketing auxiliary method and system based on a large language model. The efficiency and effect of marketing are improved by using the large language model. According to the method, by integrating a vector database, an embedded model and a context learning technology, the capabilities of real-time understanding of user intentions, personalized reply and quick service change adaptation are realized. The method has the core advantages of accurate user demand analysis, personalized service provision and efficient knowledge retrieval system. By analyzing user behaviors and dialogue records, product recommendation and marketing strategies according with user preferences can be provided. In addition, the method also has a real-time verbal skill updating capability, so that the timeliness and accuracy of information are ensured; the automatic order information extraction technology improves the information processing efficiency, and reduces the time and cost of manual operation. According to the invention, the marketing efficiency is improved, the interactive experience between the user and the customer service is enhanced, and competitive advantages are provided for enterprises in the market with intense competition.

The invention provides a customer service interaction method, an interaction device, equipment, a storage medium and a program product, and relates to the technical field of computers. The customer service interaction method based on the large language model comprises the following steps: performing intention scene recognition on a received user question; identifying that the user question belongs to a specified intention scene, and determining a corresponding domain knowledge base matched with the user question; performing enhanced retrieval on the knowledge base in the corresponding field based on the user question to obtain a business knowledge fragment for enhancing the user question; and inputting the business knowledge fragments into a large language model, so that the large language model performs filtering type question reply processing based on the business knowledge fragments, and outputs reply information of the user question based on a processing result. According to the technical scheme, the real intention of the user in continuous interaction can be deeply analyzed, the content which the user wants to consult can be more accurately grasped, and the consulting requirement of the user is better met.

The embodiment of the invention relates to the technical field of information, and discloses an automatic document generation method, system and device, a storage medium and a product. The document automatic generation method comprises the following steps: reading a to-be-processed document, and obtaining a document inner tag corresponding to the content of the to-be-processed document; analyzing the label in the document, and managing and adjusting the label in the document to obtain a target document label; filling the target document label into a document template to generate a target document; and carrying out tag classification and integration on the target document, and carrying out document tag management display in a user management interface. According to the method, the key content in the to-be-processed document is extracted, the tagging processing is performed on the document content, and then the document content is filled into the document template, so that the repeated editing work and manual modification time are greatly reduced, and the situation of error information introduced by manual operation is reduced while the document generation efficiency is improved; and the accuracy of automatic generation of the document is improved.

The invention discloses a data management system based on a monitoring video stream, belongs to the field of data analysis, and aims to solve the problems of camera connection acquisition, image quality optimization, pedestrian related information analysis and data storage retrieval and backup in video monitoring. The system comprises a data acquisition module, a target detection module and a data storage module. The data acquisition module is used for identifying and connecting a video monitoring camera, performing video stream data acquisition, adjusting an acquisition frame rate by estimating a data size, and evaluating and optimizing image quality to obtain a detection image data set; the target detection module is used for carrying out feature extraction, classification and marking on pedestrians in the detection image data set, recording pedestrian trajectory information, carrying out real-time tracking and updating, identifying a behavior mode according to the trajectory information, dividing a gathering area and obtaining the pedestrian flow; and the data storage module is used for classifying and labeling the data, constructing an index structure to guarantee efficient retrieval, dividing data grades according to multi-dimensional features, and dynamically adjusting a backup time interval.

The invention discloses a big data real-time processing system and method, and relates to the technical field of big data processing, and the big data real-time processing system comprises a data partitioning module, a data storage module, a data reading module and a data backup module; the data partitioning module is used for partitioning big data entering a block chain in real time by using a partitioning strategy, extracting keywords, and distinguishing the frequency of data blocks according to historical query records; the data storage module stores data blocks through a storage contract, encrypts identifiers of the data blocks and establishes a mapping relation; the data reading module screens data blocks based on the private key set when a user queries, and determines a sending sequence through keyword matching; the data backup module generates a backup after storage, performs different updating strategies for data blocks with different frequencies, and performs adaptive modification on original data by using a hash value; in combination with the block chain technology, multiple advantages of real-time processing, efficient storage, safe reading, flexible backup and the like are integrated, and a comprehensive and efficient solution is provided for big data processing.

The invention discloses a lyric and rhythm printing method based on an audio fingerprint and related equipment, and the method comprises the steps: carrying out the preprocessing operation of a to-be-processed audio, and obtaining the preprocessed audio data; dividing the preprocessed audio data into a plurality of segments; respectively extracting key features of each fragment; converting each key feature into a corresponding audio fingerprint through a Hash algorithm; searching audio fingerprints in a preset song library and judging whether matching succeeds or not; if the matching is successful, first primary printing information is generated, the first primary printing information comprises lyric information and rhythm information arranged according to a preset format, and the lyric information and the rhythm information are lyric information and rhythm information corresponding to the matched audio fingerprint; the first primary printing information is rendered according to a preset style, and a final printing picture is obtained; and sending the final printing picture to the printing equipment to enable the printing equipment to print the final printing picture. The lyrics and rhythms can be quickly and accurately recognized and printed, and the accuracy and efficiency are improved.

The invention relates to the field of integrated retrieval dialogues, in particular to an integrated retrieval dialogue method and system based on a large model knowledge base and a medium, and the method comprises the following steps: S1, knowledge base preprocessing: standardizing a knowledge base, including cleaning, word segmentation and stem extraction of texts in the knowledge base; s2, double filtering is carried out, a sparse retriever and a dense retriever are used for retrieving the preprocessed documents, and N documents are returned; s3, combining the preliminary results, and respectively selecting p documents with high similarity from the sparse retriever and the dense retriever; s4, performing calculation on all the selected documents by applying an RRF algorithm, and adding the obtained scores for calculation; and S5, returning a final document list according to the new ranking calculated by the RRF. The method has the advantages that a novel DFRAG technology is adopted, a dense retriever is used for double filtering, and a retrieval result is finely adjusted.

According to the construction scheme multi-modal retrieval enhancement generation method and system based on the large model, intelligent scheme writing support is provided for constructors through a natural language processing technology by means of mass building industry data and knowledge, and the construction efficiency is improved. Comprising but not limited to the steps of assisting constructors in compiling a construction scheme, providing real-time answers to problems possibly encountered in the construction process, providing optimization suggestions according to project characteristics and the like; through the application of the large model, the working efficiency of constructors can be greatly improved, the waste of human resources is reduced, and the accuracy and feasibility of a construction scheme are ensured. Besides, the model can be continuously learned and updated, and the ability of assisting in compiling question answering is continuously optimized along with the accumulation of project experience, so that the model is more widely applied to each link in the building industry in the future.

The invention relates to a static and dynamic feature fusion video and text cross-modal retrieval method. The method comprises the following steps: constructing a noun, preposition and verb set for a text; converting nouns and prepositions into text static feature representation Tsf through a text encoder, and converting verbs into text dynamic feature representation Tdf; encoding a video through a video encoder to obtain video static feature representation Vsf; calculating and normalizing an inter-frame difference sequence of adjacent frames of the video, and encoding through a video encoder to obtain a video dynamic feature representation Vdf; calculating the static similarity between the Tsf and the Vsf, calculating the dynamic similarity between the Tdf and the Vdf, and carrying out weighted average on the Tsf and the Vsf to obtain a final similarity score; for a plurality of given texts and videos, k text-video pairs with the highest similarity scores are selected as retrieval results. According to the method and the system, the accuracy and the efficiency of video and text cross-modal retrieval can be improved, and videos related to text description can be effectively retrieved from a large amount of video data.

The invention discloses an RAG-based high polymer material modification optimization method and system. The method comprises the following steps: constructing a high polymer material modification professional knowledge system; constructing a retrieval enhancement generation system, acquiring intermediate data from the professional knowledge system according to a demand input by a user, evaluating the intermediate data generated by the retrieval enhancement generation system, designing an evaluation index system, and performing natural language understanding on the intermediate data by using a large language model, analyzing the matching degree between the data content and the query requirement; inputting a modification demand or an optimization demand of a high polymer material into the retrieval enhancement generation system to obtain matching content; and performing answer generation through the matching content by using a large language model to obtain a high polymer material modification scheme or optimization scheme. According to the high polymer material modification optimization method provided by the invention, on the premise of meeting the requirements of different application scenes, the research and development efficiency is effectively improved, the number of unnecessary tests is reduced, and experimental materials and labor cost are saved.

The invention belongs to the technical field of financial informatics, and discloses a financial database construction method and system based on a large model, and the method comprises the steps: collecting and preprocessing financial data, further carrying out the feature engineering based on a processed data set, and constructing a LanZhou Model large model for self-adaptive fine adjustment. Performing tagging classification on the financial data based on the large model after self-adaptive fine adjustment; constructing a financial database according to the data labeling classification, connecting a front-end component and a rear-end component of the financial database, integrating and executing a test; based on the connection of front-end and rear-end components of a database, a monitoring strategy is deployed to track the performance of the database and formulate a feedback strategy and an optimization scheme. According to the invention, through application of detailed planning and innovative technology, efficiency and accuracy of financial data management are significantly improved, scientificity and efficiency of enterprise decision making are greatly promoted, and revolutionary revolution is brought to financial management.

The invention relates to a network protocol information retrieval method and device, computer equipment, a computer readable storage medium and a computer program product. The network protocol information retrieval efficiency can be improved. The method comprises the steps of obtaining a retrieval keyword in response to a network protocol information retrieval request; acquiring a node index and a node relation index corresponding to the information knowledge graph; the information knowledge graph comprises a first node corresponding to the network protocol information and an association relationship between the nodes, the node index records the first node associated with the keyword, and the node relationship index records an association relationship between the first node and other associated first nodes; matching the retrieval keyword with the node index, determining a second node associated with the retrieval keyword, and determining a third node and a node association relationship between the second node and the third node according to the node relationship index; and generating a node connected graph according to the second node, the third node and the node association relationship to obtain a retrieval result.

The invention discloses a large-model-based campus work order transfer method, device and equipment and a medium, relates to the field of work order processing, and is applied to a preset campus work order transfer system. Performing knowledge graph construction by using the obtained campus work order knowledge graph template, the historical campus work order information and the campus department responsibility information to obtain a target campus work order knowledge graph; performing vector conversion and historical campus work order retrieval on the to-be-processed campus work order through a preset deep learning large model and a vector database to obtain a retrieval result corresponding to the to-be-processed campus work order; and performing information analysis and department responsibility matching on the to-be-processed campus work order based on a preset deep learning large model, the retrieval result and the target campus work order knowledge graph, and completing work order transfer operation corresponding to the to-be-processed campus work order according to an obtained matching result. The work order processing quality is effectively improved, and the manual intervention cost is reduced.

The embodiment of the invention provides a power business document processing method and device, equipment, a computer storage medium and a computer program product. The method comprises the following steps: acquiring an unstructured document corresponding to an electric power business hall service system; identifying basic content blocks contained in the unstructured document based on a preset document structure rule; based on the complexity of each basic content block, determining a target server to which each basic content block is allocated from a server cluster; extracting key service information in the corresponding basic content block through the target server; and fusing the key business information into a power business knowledge graph corresponding to the power business hall service system to obtain a power business document database. According to the method, the structured processing efficiency of the power business document and the management efficiency of the power business information in the power business hall are improved.

The invention discloses an intelligent question and answer method and system based on a mineral knowledge base, relates to the technical field of artificial intelligence and data mining, and is used for solving the technical problems that an existing mineral knowledge base is poor in reasoning ability and low in mineral knowledge acquisition efficiency and accuracy. The intelligent question and answer method based on the mineral knowledge base comprises the steps of obtaining mineral knowledge; distinguishing mineral names, mineral attribute names and mineral attribute values in the mineral knowledge; establishing a mineral knowledge base data table structure and a mineral knowledge graph triple structure; the mineral knowledge base data table structure and the mineral knowledge graph triple structure are stored in a knowledge database; building a webpage interface, wherein the webpage interface is provided with a search engine and an intelligent question and answer mechanism relying on a large model; the intelligent question-answering mechanism realizes intelligent question-answering of the mineral knowledge base based on the knowledge database. The invention is used for providing the intelligent question answering method and system based on the mineral knowledge base.

The invention relates to a content video-based hypercompression storage method. The method comprises the following steps of S1, acquiring video stream data of a camera through a network; s2, for the video stream data, performing corresponding decoding according to the code stream type to generate YUV data; s3, analyzing the YUV data, determining an ROI (Region of Interest), and extracting content feature values of a plurality of moving targets and position data of images where the moving targets are located as element data of the video; the ROI is logically separated from the non-ROI, secondary high-fidelity compression is carried out on the ROI, high compression is carried out on the non-ROI, and the high compression rate of the ROI under the high-fidelity condition is achieved; s4, combining the code streams of the ROI and the non-ROI into the same frame of code stream; s5, taking the ROI metadata of each region of interest as structured description data of the frame data; and S6, sending the coded code stream and the ROI metadata to a video storage engine for intelligent video storage.

The invention belongs to the technical field of Lustre file management, and particularly relates to a method and system for improving Lustre small file management and performance, and the system comprises a nested file system, a three-level index module, a cache index module and a self-adaptive cache module; the nested file system realizes management and storage of small files; the three-level index module comprises a small file global metadata index, a container file internal index and a cache index and is used for optimizing retrieval and storage management of small files; the cache index module is used for managing small files accessed at high frequency and reducing repeated I / O requests; and according to the self-adaptive caching module, the client dynamically adjusts a caching strategy of a small file according to the file access frequency and mode, so that the reading speed of a high-frequency access file is improved, and network I / O (Input / Output) operation is reduced. The performance bottleneck of a Lustre file system during small file processing is solved through a nested file system, and the access burden of a metadata server and an object storage server is reduced through a three-level index architecture.

The invention relates to the technical field of environmental monitoring, and discloses an exclusive encrypted file format of a universal water-gas-sound-residue pollutant data acquisition instrument. File structures including a file header setting section, a data storage format definition section, a self-checking section and an encryption algorithm section are sequentially stored in a file to form an exclusive encryption file format of the universal water, gas, sound and residue pollutant data acquisition instrument, various encryption and checking measures are adopted, and the safety and integrity of data in the transmission and storage process are ensured. The method has the advantages that data are stored in the database and prevented from being tampered and stolen, data storage efficiency and retrieval speed are increased due to reasonable data storage formats and index designs, data management and analysis are facilitated, file damage or data tampering can be timely discovered through CRC32 check and data integrity check codes, data reliability is guaranteed, and data storage efficiency and retrieval speed are increased. And on the basis of an XML structured storage mode and an open file format design, subsequent addition of new pollutant parameters or function extension is facilitated, and good expandability is achieved.

The invention discloses an E-commerce customer service method and system based on Al, and the method comprises the steps: collecting the interaction data of a user on an E-commerce platform, and constructing a user portrait and user interest model; extracting commodity features in the e-commerce platform, carrying out digital processing on the commodity features to obtain digital commodity features, and calculating the similarity between the user portrait and each digital commodity feature; generating an adjacent matrix and a user feature matrix; according to the user feature matrix and the adjacent matrix, calculating a user interest vector by using a user interest model; and calculating the interest score of the user for each commodity by using the user interest vector and the digital commodity characteristics, and retrieving and pushing the user interest commodity in the customer service platform according to the similarity and the interest score, thereby realizing the customer service automatic pushing service. According to the embodiment of the invention, the method can achieve the efficient retrieval and pushing of the interested commodities of the user, improves the recommendation accuracy, can effectively improve the shopping experience of the user, and improves the competitiveness of an e-commerce platform.

The invention relates to the technical field of digital archive resources, and discloses a knowledge graph construction method and system based on digital archive resources, and the method comprises the following steps: 1, converting a paper archive into an electronic document, obtaining the digital archive resources, and extracting the content of the digital archive resources; 2, based on the extracted content, performing multiple times of identification on entities in the same electronic archive text to obtain identification result data, processing the identification result data, and calculating an identification result evaluation value; 3, based on the obtained identification result evaluation value, the identification result of the same electronic file is evaluated, and the evaluation result comprises generation of an accurate identification signal; and step 4, based on the generated accurate identification signal. According to the method, when the entities are recognized, repeated recognition is carried out for multiple times, and the result is comprehensively analyzed, so that the accuracy and reliability of entity recognition are effectively improved, and powerful support is provided for knowledge graph construction based on digital archive resources.

The invention discloses a method for quickly browsing multi-source heterogeneous mass remote sensing information in real time. Belongs to the field of remote sensing information technology application and particularly relates to the technical field of remote sensing information real-time rapid browsing. The method comprises the following steps: processing a multi-source heterogeneous remote sensing image by adopting a multivariate heterogeneous remote sensing information standardized archiving processing method, and constructing a multi-dimensional cloud storage with a place-time as an index; for an image real-time browsing request, a self-adaptive heterogeneous image tile real-time rendering method is adopted to render tiles; a multi-dimensional multi-level cache method is adopted to provide data for each link returned by tile rendering; a multi-source heterogeneous remote sensing information browsing service is provided for a user through a self-adaptive heterogeneous image tile real-time rendering technology and a multi-dimensional multi-level caching technology; according to the use habit of a user, intelligent pre-loading and intelligent cache management of tiles are realized through an intelligent cache management and pre-loading method. The technical problems of high delay and long user waiting time of non-slicing release are solved.

The embodiment of the invention relates to an image retrieval method and device, equipment and a medium. The method comprises the steps that retrieval reference information is acquired; the retrieval reference information comprises first semantic information and first pixel information; based on the first semantic information, performing retrieval from a preset semantic information library to obtain multiple pieces of candidate semantic information matched with the first semantic information; based on the candidate sample images to which the candidate semantic information belongs respectively, retrieving from a preset pixel information base to obtain candidate pixel information corresponding to the candidate sample images respectively; and selecting a target sample image from the plurality of candidate sample images according to the similarity between the candidate pixel information corresponding to the plurality of candidate sample images and the first pixel information, and taking the target sample image as a retrieval result image corresponding to the retrieval reference information. According to the embodiment, it can be effectively guaranteed that the retrieval result meets the requirement, and the retrieval efficiency is guaranteed.

The invention discloses a time sequence electroencephalogram data quality detection and restoration method and a time sequence electroencephalogram data quality detection and restoration system, and belongs to the technical field of industrial internet. According to the method, the problems that the electroencephalogram data is lost, the electroencephalogram data quality is poor and the electroencephalogram data storage efficiency is low are solved. According to the method, by calculating the integrity index of the electroencephalogram data, the hidden data value missing condition can be detected, then the data filling operation is guided according to the missing detection result, and the original electroencephalogram data characteristics can be recovered. Effectiveness indexes are established on the basis of effectiveness, change speed and acceleration of values, quantitative evaluation standards can be provided for reasonability of electroencephalogram data values so as to detect whether data points are reasonable and have sudden changes or abnormities or not, a data restoration method is further selected according to detection results, data stability is enhanced, data continuity is improved, and the accuracy of data restoration is improved. The electroencephalogram data quality is improved, and subsequent data analysis is facilitated. The method can be applied to electroencephalogram data quality detection and restoration.

The invention discloses a graph database construction method for construction land full-life-cycle management, and belongs to the technical field of GIS data storage and retrieval. According to the invention, by utilizing the flexible data model of the graph database and the analysis capability of a complex relation network, the graph database association relationship is established for the planning, batching, storage, supply and registration stages of the land parcels by modeling the land parcels and the land parcel association relationship, so that the full-life-cycle management of the land based on the graph database is realized. According to the method, a plot entity and an association relation (vertexes and edges of a corresponding graph) of the plot entity are expressed by utilizing the strong modeling capability of a graph database, and a flexible data model can adapt to continuously changing business requirements and analysis of a complex relation network, so that the purposes of full-life-cycle management of the construction land and visual, rapid and flexible display are achieved.

The invention discloses an image query method and device, a storage medium and a computer program product. The method comprises the following steps: determining a first query vector corresponding to an image feature of a to-be-queried image; querying in an image retrieval database according to the first query vector to obtain a first image set; according to the first image set, a second query vector is determined, query is carried out in an image retrieval database according to the second query vector, a second image set is obtained, and the second query vector comprises a target class query vector and a confusion class query vector; and determining an image corresponding to the target class query vector in the second image set by adopting the classification model to obtain an image query result corresponding to the to-be-queried image. According to the method and the device, the technical problem that the risk of personal privacy disclosure possibly exists due to the fact that the image provided by a querier needs to be stored on a cloud server in a plaintext form when the image similar to the query image is retrieved in an image database in the related technology is solved.