15 results about "Fingerprint retrieval" patented technology

The invention discloses a similar weather retrieval method based on physical alignment fingerprints, and the method comprises the steps: obtaining a constructed fingerprint database and the time-space sequence data of a target meteorological field corresponding to the to-be-queried weather, and enabling the fingerprint database to be constructed through fingerprints generated by the time-space sequence data of the meteorological field corresponding to a plurality of historical weathers; performing physical consistent double-view contrast learning on the time-space sequence data of the target meteorological field to generate a first physical enhancement double-view result corresponding to a scalar field and / or a second physical enhancement double-view result corresponding to a vector field; inputting the first physical enhancement double-view result and / or the second physical enhancement double-view result into a trained fingerprint generation model to obtain a query fingerprint; retrieving a plurality of fingerprints similar to the query fingerprint in a fingerprint database to obtain a fingerprint retrieval result; and finding out a plurality of corresponding target historical weathers according to the fingerprint retrieval result, and taking the plurality of target historical weathers as similar weather retrieval results. The accuracy of similar weather retrieval can be improved.

The invention relates to the technical field of electronic payment, in particular to an automatic recharging system based on AI message recognition, which comprises an information extraction module, a screening composite message, a text construction character string, a decoding image construction gray matrix and a timestamp generation module, a voucher analysis module, an interception declaration numerical value and an account identifier, and a recharging module. An image generation voucher amount, a serial number and generation time are identified; a logic risk control module establishes an amount consistency and uniqueness mark; a verification instruction is generated based on a time interval and the mark; and an instruction execution module constructs a recharge message and sends the recharge message to a payment gateway. According to the method, the text and image features are independently extracted, the unstructured voucher is converted into calculable elements, the multi-dimensional risk control logic based on amount comparison, fingerprint retrieval and failure judgment is constructed, counterfeited or repeated requests are blocked without manual intervention, and automatic closed loop from message recognition to fund injection is achieved; and the accounting processing accuracy and security are improved.

This invention discloses a firewall rule query method based on a cuckoo filter, comprising the following steps: S1, firewall fingerprint collection; S2, firewall fingerprint comparison; S3, firewall fingerprint storage; S4, firewall fingerprint retrieval; S5, information parsing and comparison. This invention, by constructing firewall fingerprints using a novel cuckoo filter-based approach, achieves high-performance query capabilities. Furthermore, the fingerprints can be stored in minimal quantities, are reusable, and load quickly, enabling rapid statistical analysis of security rule coverage for millions of hosts in firewall management.

This application discloses a fingerprint retrieval method, apparatus, non-volatile storage medium, and electronic device. The method includes: determining the minutiae distribution and orientation map of a fingerprint image to be retrieved, wherein the minutiae distribution and orientation map represent the distribution and orientation information of the minutiae in the fingerprint image; processing the fingerprint image and the minutiae distribution and orientation map using a fingerprint feature extraction neural network to obtain a feature vector of the fingerprint image to be retrieved, wherein the length of the feature vector is a preset length; and determining a set of candidate fingerprint images in a fingerprint database based on the feature vector. This application solves the technical problem of low fingerprint retrieval efficiency caused by the manual design of feature vectors for fingerprint images in related technologies.

The application discloses a large-scale fingerprint retrieval method based on a graph model, and belongs to the technical field of fingerprint retrieval, and comprises the following steps: step 1, a training data set is constructed, and a fingerprint feature extraction algorithm is used to obtain the fingerprint features of each fingerprint; step 2, a fingerprint graph structure is constructed, and conversion of the fingerprint features to the fingerprint graph structure is realized; step 3, a graph neural network is constructed, the fingerprint features are deeply characterized, and graph embedding is used as a final feature format; step 4, the graph neural network is trained, and a fingerprint graph model is obtained; and step 5, performance of the fingerprint graph model is tested. In the method, the graph model is constructed based on the fingerprint features, the graph neural network is used to extract the inherent correlation structure between the topological relationship between the fingerprint feature points and the fingerprints, the existing surface geometric structure is broken through, the graph paradigm fingerprint deep features that have not been considered by people are fully captured, the accuracy of retrieval is significantly improved, and the efficiency of the fingerprint retrieval method is improved by using the deep learning technology.

The application provides a method and device for realizing multi-modal reasoning acceleration by algorithm power reuse Token through an intelligent computing cloud platform, relates to the technical fields of intelligent computing centers, intelligent computing centers, algorithm power infrastructure and intelligent computing cloud, and the method comprises the following steps: receiving multi-modal visual content for standardized processing to obtain at least one visual content block; generating Token fingerprints from multiple complementary hashes of each visual content block to retrieve candidate caches; based on attribute information associated with the current request for the visual content, if attribute information and metadata of the candidate cache are successfully matched, calling the algorithm power of the intelligent computing cloud platform to obtain Token and / or Token-KV; according to the prompt word of the current request, the position mapping parameter and the bridging Token of the candidate cache, performing position remapping and bridging Token recalculation to reason the current request. The efficiency and reliability of Token reuse can be improved, and the algorithm power consumption can be reduced.

This invention relates to the field of electronic payment technology, specifically to an automatic recharge system based on AI message recognition. The system includes: an information extraction module for filtering composite messages, extracting text to construct strings, decoding images to construct a grayscale matrix and generate timestamps; a voucher parsing module for extracting declared values ​​and account identifiers, recognizing images to generate voucher amounts, serial numbers, and generation times; a logical risk control module for establishing consistency and uniqueness markers for amounts, generating verification instructions based on time intervals and markers; and an instruction execution module for constructing recharge messages and sending them to the payment gateway. In this invention, by independently extracting text and image features, unstructured vouchers are transformed into computable elements. A multi-dimensional risk control logic based on amount comparison, fingerprint retrieval, and invalidation determination is constructed, blocking forged or duplicate requests without human intervention. This achieves an automated closed loop from message recognition to fund injection, improving the accuracy and security of accounting processing.

The application provides a fingerprint retrieval method and device, the method comprising: constructing a contrast learning network; reading a plurality of first pictures, and performing picture reconstruction on each first picture to form a second picture respectively, wherein the first pictures contain first fingerprint information; inputting the plurality of first pictures and the second pictures into the contrast learning network to obtain first output data and second output data corresponding to each pair of first picture and second picture respectively; calculating the similarity of each corresponding first output data and second output data; updating the weight information of a first network in the contrast learning network based on the similarity; updating the weight information of a second network in the contrast learning network based on the updated weight information of the first network, thereby obtaining a fingerprint identification network storing first fingerprint information on all the first pictures; inputting second fingerprint information into the fingerprint identification network; and completing the retrieval of the second fingerprint information based on at least the fingerprint identification network.

This invention discloses an integrated management system for equipment health management (PHM) operation software for vehicle platforms, specifically relating to the field of vehicle health management and collaborative control of operation software. It addresses the problem that existing health conclusions are difficult to accurately apply to the current operating state after changes in the target subsystem software state. By collecting the target software cluster version identifier, parameter set summary, health anchor value, fault event count, and operating condition bucket label, a current software state fingerprint is generated. A verified PHM reference template corresponding to the current software state is retrieved. Based on freezing the health conclusions prior to the change, continuous verification is performed on the health anchor value and fault event count. The PHM configuration is switched or anomaly handling instructions are output based on continuous consistency counts or continuous mismatch counts, thereby completing the continuity maintenance of PHM conclusions during vehicle platform state change phases.

This invention relates to a time-series kinship chain fingerprinting method and system resistant to feature drift. The method includes: identifying field information in a data entity that can be used for fingerprint recognition as feature factors; preprocessing the corresponding original feature data to obtain multi-dimensional vector data; generating base blocks of a target length from the multi-dimensional vector data according to time slices, where time slices are collected periodically or triggered when features change, with timestamps in UTC millisecond format; setting the target length as needed based on the number of feature factors and hash algorithm type in the actual scenario; concatenating the base blocks into a one-way hash chain to obtain a time-series kinship chain; forming a time-series kinship database by indexing all time-series kinship chains using the root fingerprint of the kinship chain; collecting feature data corresponding to the feature factors in the current data entity; performing kinship fingerprint retrieval on the feature data using the time-series kinship database; and generating a root data fingerprint. This invention utilizes publicly collectable information to ensure fingerprint stability.

The invention relates to the technical field of data processing, and discloses a text data set redundancy cleaning method and system based on semantic fingerprints. The method is used for solving the problems that a traditional method lacks semantic understanding and self-adaptive strategies, redundant texts are easy to leak or mistakenly delete, the manual dependence is high, and the efficiency is low. The method comprises the following steps: firstly, carrying out standardized preprocessing on batch texts, labeling languages and fields, and generating semantic representation and semantic fingerprint storage indexes; counting redundancy density and length distribution according to batches to generate a feature portrait, and solidifying threshold gears, slice granularity and grading parameters; based on fingerprint retrieval candidate pairs, short text accurate judgment and long text slicing, redundant fragment positioning and shunting automatic processing or manual rechecking are carried out; and rejecting, cutting or marking, recording a log and a rollback entry according to shunting, and completing traceable and rollback redundancy cleaning.

This application discloses a medical data processing method, apparatus, equipment, and medium based on a medical industry knowledge base and context-awareness, relating to the computer field. The method includes: constructing a medical industry knowledge base; acquiring the fields and metadata information of the medical data to be processed; determining field fingerprints based on the fields and corresponding metadata information; retrieving field fingerprints; matching the search results with the fields of the medical data to be processed; determining whether a corresponding rule exists; if not, inputting the fields of the medical data to be processed, metadata information, and a classification and grading framework into a target medical data classification model to obtain a first data classification result; using the first data classification result of the target table as target context data; and generating a second data classification result based on the target context data using the target medical data classification model, so that the user can obtain and check the second data classification result to obtain the target medical data classification result. This improves the accuracy of data classification.

The application discloses a kind of based on player behavior log's syntax tree structure automatic marking and behavior mode mining method and system.The method is washed to player behavior log, conversation segmentation and terminal symbol mapping, based on behavior grammar constructs compressed analysis forest and establishes shared subtree index;Convergent state is retrieved to warm start inference by constructing residual fingerprint history;On analysis forest, adopt alternating direction multiplier method to carry out production consistency, stage monotonicity and resource boundary multiple constraint inference, output node label posteriori and residual tensor aligned according to node-production-constraint type;Stable syntax tree is normalized and encoded and frequent subtree mining, generate behavior mode library and failure positioning mapping with certificate.The scheme improves the consistency and interpretability of marking, reduces the cost of manual and iteration, and improves the controllability of mode online trigger.

The invention discloses a syntax tree structure automatic labeling and behavior pattern mining method and system based on player behavior logs. According to the method, cleaning, session segmentation and terminator mapping are carried out on player behavior logs, a compression analysis forest is constructed based on behavior grammar, and a shared sub-tree index is established; constructing a residual fingerprint retrieval historical convergence state to warm start inference; performing multi-constraint inference such as productive consistency, stage monotonicity and resource boundary on the analysis forest by adopting an alternating direction multiplier method, and outputting a node tag posteriori and a residual tensor aligned according to a node-productive-constraint type; and performing normalized coding and frequent sub-tree mining on the stable syntax tree to generate a certificate carrying behavior pattern library and failure positioning mapping. According to the scheme, the labeling consistency and interpretability are improved, the labor and iteration cost is reduced, and the controllability of mode on-line triggering is improved.

This invention discloses a method for dynamic configuration and rendering of heterogeneous data fields in AI-powered intelligent CRM that supports multiple business scenarios. It relates to the field of data processing technology, and includes: collecting heterogeneous fields and access contexts from multiple business scenarios; constructing an original field event set and generating field semantic fingerprints; retrieving a standard field semantic library based on the semantic fingerprints to generate a unified standard field set; then combining business scenarios to complete field filtering, permission constraints, and conflict resolution, forming an effective field state set; further constructing a field dependency graph to complete page arrangement, component mapping, and initial interface rendering; finally, in runtime, performing local propagation based on field changes to achieve incremental reconfiguration and local re-rendering of fields. This method achieves semantic-level unified normalization and local incremental dynamic configuration rendering of heterogeneous CRM fields in multiple business scenarios, improving the accuracy of field configuration and the efficiency of page linkage response.