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52results about How to "Avoid error propagation" patented technology
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Time sequence processing method and device for distributed target InSAR with enhanced space-time coherence
ActiveCN110412574AReduce uncertaintyReduce biasRadio wave reradiation/reflectionQualitative analysisPermanent scatterer
The invention discloses a time sequence processing method and device for a distributed target InSAR with enhanced space-time coherence. The method comprises the steps of carrying out threshold separation on a permanent scatterer (PS) and a distributed scatterer (DS) on the basis of an obtained single complex image data stack; performing phase stability analysis on separated PS candidate points bymeans of a StaMPS approach to obtain PS points; carrying out covariance matrix estimation on DS candidate points one by one through a maximum likelihood estimator and refining a covariance matrix through a bootstrapped coherence estimator; performing time sequence phase optimization on each DS candidate point; selecting DS points; constructing a two-layer network for the selected PS and DS points;carrying out phase error separation on an unwrapping phase after three-dimensional phase unwrapping is performed on the PS points and the DS points; utilizing the maximum likelihood estimator and a phase model to estimate geophysical parameters. The method can reduce the uncertainty of InSAR time sequence analysis caused by coherence loss and an ill-conditioned matrix, improve the quality controlof time sequence data processing and thus improve the estimation precision and reliability of products.
Owner:HOHAI UNIV
Method and system for reconstructing magnetic resonance parameters
ActiveCN102663701AQuality improvementAvoid mistakesImage enhancementSparse constraintMathematical model
A method for reconstructing magnetic resonance parameters includes the steps: acquiring diffusion-weighted imaging K space data according to a random descending acquisition matrix; establishing a diffusion-weighted imaging mathematical model containing a dispersion tensor coefficient; defining an objective function, fitting the dispersion tensor coefficient by solving an optimization problem and adding sparse constraint; and solving the dispersion tensor coefficient according to the descending acquired data to minimize the objective function. In the method for reconstructing the magnetic resonance parameters, DWI (diffusion-weighted imaging) images do not need to be reconstructed, the dispersion tensor coefficient is directly obtained from the descending acquired K space data by means of calculation, mistaken fitting of the dispersion tensor coefficient caused by errors introduced in reconstruction of the DWI images is avoided, and error propagation is prevented. The invention further provides a system for reconstructing the magnetic resonance parameters.
Owner:SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
Magnetic resonance parameter imaging method and system
ActiveCN103705239AImaging is fast and accurateAvoid error propagationDiagnostic recording/measuringSensorsRelational modelMaximum a posteriori estimation
A magnetic resonance parameter imaging method includes the steps of acquiring an under-sampling signal corresponding to a magnetic resonance image sequence on a magnetic resonance imager; estimating and solving a parameter image and proton density distribution function of biological issue through sparsity in parameter image and proton density distribution functions and model-based maximum posterior probability. The under-sampling signal is formed by application of magnetic resonance parameter imaging on the biological issue. A model for maximum posterior probability is a model of relation between the magnetic resonance image sequence and the parameter image and proton density distribution function. The method has the advantages that the parameter image and proton density distribution function of the biological tissue is directly estimated through the under-sampling signal and error propagation caused by the application of an under-sampling rebuilt magnetic resonance image in estimating biological tissue parameters is avoided. The sparsity in the parameter image and proton density distribution function is introduced, and image artifacts caused by under-sampling can be effectively suppressed. In addition, the invention further provides a magnetic resonance parameter imaging system.
Owner:SHENZHEN INST OF ADVANCED TECH
End-to-end context-based knowledge base question and answer method and device
ActiveCN110059160AIncrease diversityAvoid error propagationNeural architecturesText database queryingEntity linkingGranularity
The invention discloses an end-to-end context-based knowledge base question and answer method and device, and the method and device consider the connection relationship between entities and relationships in a knowledge base, enable the two tasks including entity links and relationship prediction contained in the knowledge base to be mutually promoted, and jointly improve the two tasks. The methodmainly comprises the steps of prreprocessing a problem and removing special symbols; constructing a candidate entity set related to the problem based on the knowledge base, and constructing a candidate relationship set according to the relationship of the candidate entities in the knowledge base; for each entity in each candidate set, extracting the context of the entity in the question; dividingthe candidate relationships into different granularities; predicting a subject entity and a predicate relationship based on the CERM model; and finding the object entity in the knowledge base as an answer to return by using a predicted subject entity and relationship. Entity links and relationship prediction in knowledge base questions and answers are integrated into a unified prediction model. Joint prediction of the subjective entities and relationships is achieved, and accuracy of questions and answers is improved.
Owner:SOUTHEAST UNIV
Knowledge graph-based patient medical record similarity evaluation method and system
PendingCN112364174AImprove accuracyImprove recognition accuracySemantic analysisNeural architecturesMedical recordEntity type
The invention provides a knowledge graph-based patient medical record similarity evaluation method and system. The method comprises the steps of obtaining and preprocessing patient medical record textdata; carrying out entity identification and entity relationship extraction on the preprocessed data by adopting a joint information extraction model based on weak supervised learning, and expressingan obtained medical entity type by using a knowledge vector; constructing triples in the knowledge graph according to the obtained entity relationship, and representing the triples by using a joint knowledge vector; combining the knowledge vectors into the same semantic space by utilizing the joint vector, and judging the similarity by calculating the semantic distance between entities; accordingto the method, important knowledge in the electronic medical record is mined and extracted by using the bidirectional recurrent neural network for multiple times, the subject domain knowledge graph concept is expanded to the medical field, entity identification and relationship extraction are performed under the current situation that the medical entity type is relatively limited, and the accuracy of similarity evaluation is improved.
Owner:SHANDONG UNIV
Method and device for precoding in multi-user MIMO (multiple input multiple output) system
ActiveCN102710390ASmall amount of calculationHigh speedError prevention/detection by diversity receptionSpatial correlationCo-channel interference
The invention discloses a method and a device for precoding in a multi-user MIMO (multiple input multiple output) system. The method includes receiving pilot signals of users; computing spatial correlation matrixes according to the received pilot signals, and computing guiding matrixes of expected users according to the received pilot signals and pilot signals transmitted by the users; and computing precoding matrixes of the expected users according to inverses of the spatial correlation matrixes and the guiding matrixes. The method and the device have the advantages that computational complexity of precoding can be effectively reduced, and precoding also can be effectively carried out under the condition of co-channel interference which stops acquisition of channel information.
Owner:北京万海云科技有限公司
Online measurement device and measurement method for NO concentration in high-NO2 and low-NO atmosphere
ActiveCN106644986ARealize online measurementAccurate online measurementColor/spectral properties measurementsAir quality improvementMeasurement deviceMeasuring instrument
The invention discloses an online measurement device and measurement method for the NO concentration in a high-NO2 and low-NO atmosphere. The online measurement device comprises an ozone generation unit, a connection pipe cleaning unit and a sampling pipe, wherein a connection reaction bin, an NO2 measuring instrument, a second mass flow meter and a first air pump are sequentially connected behind the sampling pipe; and the connection pipe cleaning unit comprises an electromagnetic three-way valve, an activated carbon tube, a current-limiting hole and a second air pump. By adopting a cavity-enhanced absorption spectroscopy, a sampling mode (actual atmosphere of ozone is added) or a zero point mode (actual atmosphere) is set through the electromagnetic three-way valve; absorption spectrum intensity signals of two modes are measured through an NO2 measuring instrument as a sampling spectrum and a reference spectrum respectively, and then NO in the atmosphere is converted into a concentration value of the NO2 through spectral fitting, that is to say, measurement of the NO concentration in the atmosphere environment is achieved, so that the online measurement device and measurement method have the characteristics of being free of NO2 concentration interference, a low detection limit, high sensitivity, high temporal-spatial resolution, high stability and low cost.
Owner:PEKING UNIV
Three-dimensional reconstruction system calibration method based on multi-frequency structured light
The invention discloses a three-dimensional reconstruction system calibration method based on multi-frequency structured light. The calibration method comprises the following steps of step S1, initializing equipment; step S2, preparing a calibration board; step S3, acquiring a calibration image; step S4, calibrating a camera; step S41, determining kp0; step S42, determining kp1 and kp2; step S43,determining kp3 and kp4; step S44, searching the remaining of small circles; step S5, calibrating a projector; step S51, generating a G matrix by using a calibration board white-light chart; step S52,unwrapping phase; step S521, acquiring a grating projection chart; step S522, unwrapping the phase; step S523, iteratively computing to obtain the finest stripe absolute phase; step S53, solving parameter; and step S6, ending. The calibration method provided by the invention has the advantages of being simple in calibration process, high in accuracy, strong in practicability, convenient to use and low in cost.
Owner:FOSHAN NANHAI GUANGDONG TECH UNIV CNC EQUIP COOP INNOVATION INST +1
Intelligent question answering method based on depth learning
InactiveCN109063164AAvoid error propagationReduce complexityNeural architecturesNeural learning methodsModel predictionDeep learning
The invention discloses an intelligent question answering method based on depth learning, comprising the following steps: step 1, collecting original conversation data; Step 2, data preprocess, 3, construct a Seq2seq model, establishing an encode layer (Encoder) and a decoding lay (Decoder), and connecting that Encoder layer and the Decoder layer to obtain the Seq2seq model; 4, model prediction, wherein that model prediction is a Seq2seq model construct according to the above, and aft the Seq2seq model is trained with the original conversation data, the problem data is taken as input, and themodel automatically generates comment data. Through deep learning, the problem is directly mapped to the answer, so as to optimize the whole question answering method, avoid the problem of error transmission, and greatly reduce the complexity of the system.
Owner:百卓网络科技有限公司
Family atlas automatic construction method based on multi-task joint neural network model
ActiveCN110532398AAvoid error propagationReduce redundancyNeural architecturesNeural learning methodsData fieldNetwork model
The invention discloses a family atlas automatic construction method based on a multi-task joint neural network model. The method comprises the following steps: firstly, establishing the multi-task joint neural network model; training an end-to-end joint neural network model; optimizing the end-to-end joint neural network model to obtain a final model; and finally, constructing a family atlas through the final model. According to the multi-task joint model disclosed by the invention, relationship classification between every two entities is avoided, and the redundancy of model output is greatly reduced. The joint extraction method provided by the invention can also be applied to other data fields, and can reflect good time efficiency and accuracy on an information extraction task. According to the method, the performance of entity extraction and relationship classification tasks is improved from two aspects of efficiency and precision, and the method can be flexibly expanded to other tasks needing entity extraction except for family atlas construction tasks and performing relationship classification.
Owner:XI AN JIAOTONG UNIV
Quality map weighting based multi-baseline least-square phase unwinding method
ActiveCN110109100AImprove unwrapping accuracyAvoiding phase error propagation problems at residual pointsRadio wave reradiation/reflectionPrior informationPhase gradient
The invention discloses a quality map weighting based multi-baseline least-square phase unwinding method. According to the method, a first-order phase gradient principal value in the winding phase ofa multi-baseline InSAR is calculated, and is extended in mirror symmetry, a second-order phase gradient is calculated, a quality map is used to determine the quality of the winding phase, the windingphase as prior information is used to carry out phase compensation on residual error points in the winding phase, the second-order phase gradient of the winding phase is optimized and weighted on thebasis of the quality map, and multi-baseline least square phase unwinding is carried out to obtain the unwinding phase. Multi-baseline measurement enriches interference phase information of the targetscene, the problem in transferring the phase error of a residual error point in a traditional single-baseline least square phase unwinding algorithm is solved, and the phase unwinding precision is improved.
Owner:UNIV OF ELECTRONIC SCI & TECH OF CHINA
Non-inductive three-dimensional face reconstruction method and acquisition reconstruction system
ActiveCN112308963AHigh precisionReduce demandDetails involving processing stepsImage enhancementRing typeEngineering
The invention relates to the field of face image processing, in particular to a non-inductive three-dimensional face reconstruction method and an acquisition reconstruction system. According to the reconstruction method provided by the invention, a circular ring type double-circle-center calibration plate is used for calibration, an implicit function method is used for global fusion and curved surface reconstruction, and the three-dimensional curved surface model is subjected to smooth processing and optimization, so that the precision of a final output image is greatly improved, and the requirement on equipment is also reduced. Meanwhile, a three-stand-column type instrument structure is adopted, installation is convenient, the size of the instrument is reduced, the stability of the instrument is improved, the designed structure is simpler and more convenient through modularization, rapid production is facilitated, and the cost is greatly reduced; according to the invention, the target human face is acquired through the three acquisition units, and fine matching of homonymous points is realized, so that the resolution of a three-dimensional object is increased, the reconstructionprecision of three-dimensional data is improved, and the speed of human face acquisition and three-dimensional reconstruction is also improved.
Owner:WISESOFT CO LTD
Method for extracting event argument in text and electronic equipment
ActiveCN114297394ASolve the problem of inaccurate extractionAchieve precise positioningText database clustering/classificationSemantic tool creationEvent typeTarget text
The invention relates to a method for extracting an event argument in a text and electronic equipment, and the method comprises the steps: detecting an event type contained in a to-be-processed text, and obtaining a target event type; constructing and obtaining an argument extraction problem according to the target event type and the prior association information of the corresponding target argument role; splicing the to-be-processed text and the argument extraction problem to obtain a target text; the representation vector of the target text is input into a machine reading understanding model, the model comprises two layers of classifiers which are arranged in sequence, the first layer of classifier synchronously identifies and predicts whether an answer exists in the target text or not and identifies and predicts the starting position and the ending position of the answer, and a position prediction result carrying an answer indication label is obtained; the second-layer classifier predicts whether the prediction entity is an event argument or not after the start position and the end position are paired and combined, and an answer prediction result is obtained; and outputting the event argument according to the answer prediction result and the corresponding label.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
A biomedical event jointed extraction method based on a replication mechanism
ActiveCN109446326AAvoid the disadvantages of being independent of each otherAvoid error propagationSemantic analysisCharacter and pattern recognitionCopying mechanismPhases of clinical research
The invention provides a biomedical event extraction method based on a replication mechanism, belonging to the technical field of natural language processing. The biomedical event extraction method based on the replication mechanism comprises the steps of constructing a model input vector; constructing an Encoder module using a bi-directional LSTM model; constructing a Decoder module based on an Attention mechanism and a replication mechanism to recognize triggers and elements at the same time. The method of the invention can effectively avoid the disadvantages of cascading error and independence between subtasks caused by the staged method, and error transmission caused by the simple use of shared parameters in the joint model, thereby improving the performance of biomedical event extraction.
Owner:DALIAN UNIV OF TECH
MODIS-based PM2.5 remote sensing inversion method
ActiveCN108170927AAvoid error propagationHigh precisionDesign optimisation/simulationMachine learningImaging processingPerformance index
The invention relates to the field of remote sensing image processing, and in particular to an MODIS-based PM2.5 remote sensing inversion method. The method comprises the following steps of: obtainingan MODIS image and PM2.5 monitoring data at the same time; interpolating the PM2.5 data into a PM2.5 interpolation image; constructing a training set and a test set; using the training set to train amachine learning algorithm, using a trained model to the test set, and calculating a performance index, on the test set, of the model; repeating the steps S3 and S4 to obtain a plurality of performance indexes so as to select an optimum model; and using the optimum model to the whole MODIS image so as to obtain a PM2.5 inversion result of the whole MODIS image. The method starts from data of remote sensing images and directly establishes a relationship between the remote sensing images and measured PM2.5 through the machine learning algorithm, so that error transfer is avoided and inversion results with higher precision are achieved. The method has the effects of avoiding error transfer and being high in inversion precision.
Owner:SHENZHEN INST OF ADVANCED TECH
Model training method and device, and method and device for realizing text processing
The invention discloses a model training method and device and a method and device for realizing text processing, and the method comprises the steps: for a preset number of input data which completesword segmentation and part-of-speech tagging, taking a character as a unit to identify a character contained in each chunk and the part-of-speech of each character; training the identified input datathrough a preset training model to obtain a text processing model for performing word segmentation and part-of-speech tagging on the to-be-processed text; and performing word segmentation and part-of-speech tagging on the to-be-processed text through the obtained text processing model. According to the embodiment of the invention, word segmentation and part-of-speech tagging are carried out at thesame time through text processing, and error transmission in the word segmentation and part-of-speech tagging process is avoided.
Owner:BEIJING MININGLAMP SOFTWARE SYST CO LTD
Fine-grained numerical information extraction method based on joint learning model
ActiveCN111309849AImprove generalizationAvoid error propagationSemantic analysisOther databases queryingFeature extractionAlgorithm
The invention discloses a fine-grained numerical information extraction method based on a joint learning model. The fine-grained numerical information extraction method comprises the following steps:preprocessing an input text; candidate numerical values are recognized according to the numerical value correlation regular expression, and the numerical values serve as trigger words and are splicedwith front and back lexical examples of the trigger words to serve as input of a joint learning model; accessing the bottom layer of the joint learning model to a word embedding layer, and adding theposition information of a numerical trigger word to the output of the word embedding layer to obtain the final distributed representation of each lexical example; accessing a subsequent feature extraction network based on distributed representation, and respectively accessing networks of specific tasks at a high level: accessing a classification network to obtain a semantic type of numerical information, and accessing a sequence labeling network to obtain a plurality of semantic roles related to numerical trigger words; combining outputs of specific tasks to obtain a numerical information unit; for a plurality of numerical information units, the composite relationship between the numerical information units is judged based on a statistical method. The method does not need artificial designfeatures, and is high in accuracy and strong in generalization ability.
Owner:NANJING UNIV
Classification method and device for multi-level classification objects
PendingCN111832589AImprove classification accuracyReduce complexityCharacter and pattern recognitionClassified informationClass model
The invention discloses a classification method and device for multi-level classification objects, and relates to the technical field of computers. One specific embodiment of the method comprises thefollowing steps: constructing a cascade classification model step by step in a joint training mode by utilizing sample feature data of multi-stage classification objects, and a construction process: constructing a first-stage cascade classification model according to a first-stage sub-classifier; when K is larger than or equal to 2 and smaller than or equal to N, the sample feature data of the multi-level classification objects and K-1-level classification information, output by the K-1-level cascade classification model, of the multi-level classification objects are jointly input into a Kth-level sub-classifier, so that the K-1-level cascade classification model and the Kth-level sub-classifier are jointly trained, and a K-level cascade classification model is obtained; and classifying the to-be-classified data of the multi-stage classification object by utilizing the final N-stage cascade classification model to obtain N-stage classification information. According to the embodiment,the inter-class hydrophilicity and hydrophobicity are considered, the classification effect is good, error transfer can be avoided, the classification accuracy is improved, the overall model complexity is low, and the model development difficulty and workload are reduced.
Owner:BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
Differential decoding method in short-range wireless network
InactiveCN101902424AImprove accuracyAvoid estimation errorEnergy efficient ICTMulti-frequency code systemsDecoding methodsFrequency shift
The invention relates to a differential decoding method in a short-range wireless network, belonging to the technical field of wireless communication. Firstly, the characteristic of cycle repetition of a transmission pilot frequency sequence is utilized to carry out front and back conjugation correlation and accumulation on a received pilot frequency digital signal, thus a reference differential correlation value is obtained; the local spread spectrum modulation sequence is subject to the same operation of front and back conjugation and accumulation so as to obtain a conjugation correlation value; the conjugation correlation value and the reference differential correlation value are related to obtain a complex number correlation value; and according to the characteristics of positive number and negative number of the real part of the complex number correlation value, data decoding is realized. The differential decoding method of the invention lowers decoding calculated amount and improves data decoding performance under the influence of frequency shift, so that a receiver has lower power dissipation and the receiving performance under bigger frequency shift, thus avoiding the error code transmission problem of the traditional differential decoding.
Owner:BEIJING TRANSPACIFIC IP TECH DEV
End-to-end quality enhancement method and device based on binocular stereo image
ActiveCN110399881AGuaranteed rateGuaranteed accuracyCharacter and pattern recognitionShort-term memoryFeature extraction
The embodiment of the invention discloses an end-to-end quality enhancement method and an end-to-end quality enhancement device based on a binocular stereo image. The method comprises the steps of respectively inputting low / high-quality images in the binocular stereo images into a feature extraction network for feature extraction; respectively inputting the obtained shallow feature maps of the low / high-quality images into an information distillation network for information distillation; and then inputting the obtained high-level feature map of the low / high-quality image into an information fusion network for information fusion, finally inputting the obtained fusion feature map into a long short-term memory network to learn the visual difference of the three-dimensional image, and reconstructing to obtain a quality enhanced image of the low-quality image. According to the invention, an end-to-end image quality enhancement algorithm is adopted. High-quality images are used for guiding low-quality image reconstruction. The visual difference of the three-dimensional images is learned through the long-term and short-term memory network based on information fusion. The operation speed can be increased. The error transmission can be avoided. The speed and accuracy of image reconstruction are guaranteed, and the consumption of internal storage and computing resources is reduced.
Owner:SHENZHEN UNIV
Video key position determination method and device
ActiveCN107222746AAchieve positioningAvoid error propagationDigital video signal modificationFrame differenceFrame sequence
The embodiment of the invention provides a video key position determination method and device. The video key position determination method comprises the following steps: acquiring a frame difference between every two adjacent video frames in a video frame sequence; acquiring a first frame difference maximum of the frame differences within a set range of the video frame sequence; and if the first frame difference maximum is located within a first area range of the set range, determining the position of the first frame difference maximum as a current key position of the video frame sequence, wherein the set range comprises the first area range and a second area range, and the length of the first area range is larger than the length of the second area range. The method and device adopting the technical scheme has the advantages that a video key position can be effectively determined, error propagation is avoided, and high robustness is achieved.
Owner:TRS INFORMATION TECH CO LTD
Zero- reference position detection method and device, equipment and computer readable storage medium
ActiveCN111414758AImprove recognition accuracyImprove final accuracyCharacter and pattern recognitionNatural language data processingAlgorithmTheoretical computer science
The invention relates to the technical field of natural language processing. The invention discloses a zero-reference position detection method and device, equipment and a computer readable storage medium, and the method comprises: splicing an input text with a to-be-detected statement needing zero-reference position detection so as to obtain a target text, and carrying out the representation of characters and features in the target text according to a preset form so as to obtain all representation matrixes; respectively embedding each representation matrix into the low-dimensional dense representation matrix, and adding the low-dimensional dense representation matrixes migrated into the representation matrixes to obtain each target dense representation matrix; sequentially inputting eachtarget dense representation matrix into a language representation model for model training to obtain a word vector corresponding to each word; and inputting each word vector into a CRF for prediction,and determining a zero-exponential position of the to-be-detected statement according to a prediction result. The technical problem that in the prior art, when zero-reference position detection is carried out, the recognition precision is low is solved.
Owner:PING AN TECH (SHENZHEN) CO LTD
Integrated multi-user detection method and system based on signal virtual processing
ActiveCN112217549AEasy to handleAvoid error propagationRadio transmissionTransmission monitoringTransposerReal-time computing
The invention discloses an integrated multi-user detection method and system based on signal virtual processing, wherein the method comprises the steps: calculating the channel ambiguity by a common receiver according to the channel state information corresponding to a transmitter of a to-be-detected signal and the modulation mode of the transmitter, and carrying out the descending sort of the channel ambiguity; if the maximum ambiguity of the channel is not zero, detecting the to-be-detected signal which does not exceed the number of antennas of a receiver in a zero-forcing mode, and eliminating the detected signal from the received mixed signal; if the maximum ambiguity of the channel is zero, enabling all the signals to be detected to be equivalent to a structured equivalent signal, then determining a symbol combination possibly carried by the signals to be detected, recovering a data symbol carried by the signals sent by the transmitter with the maximum channel gain in a zero forcing mode, and taking the data symbol as a reference symbol; and determining a symbol combination carried by the signals to be detected. Therefore, multi-user detection is realized by using a small number of antennas, and the detection efficiency is improved.
Owner:XIDIAN UNIV
Semantic analysis method and system, equipment and readable storage medium
PendingCN112765993AAvoid error propagationImprove matchSemantic analysisNeural learning methodsData classAnalysis data
The invention discloses a semantic analysis method and system, equipment and a readable storage medium. The semantic analysis method comprises the following steps: step 1, collecting and cleaning data to be processed; 2, constructing a deep learning model, inputting to-be-processed data into the deep learning model, extracting elements from the to-be-processed data, and obtaining a data category of the to-be-processed data; 3, matching a mapping table corresponding to the data category, inputting the extracted elements into the mapping table for mapping, and obtaining semantic logic corresponding to the to-be-processed data; and 4, matching analysis data conforming to the semantic logic in a database, and outputting the analysis data. According to the method, the spoken question sentence can be analyzed and converted into the database language, and the data conforming to the intention of the question sentence can be obtained through matching.
Owner:SHANGHAI DATATOM INFORMATION TECH CO LTD
Seabed horizontal array shape correction method and processor
PendingCN113721245AReduce parameter dimensionCalibration results are reliableAcoustic wave reradiationGenetics algorithmsEngineering
The embodiment of the invention provides a seabed horizontal array shape correction method and device, a processor and a storage medium. The method comprises the following steps: transmitting a cooperative sound signal through a transmitting point corresponding to a seabed horizontal array laying sea area; according to the cooperative sound signal, obtaining an area position where the seabed horizontal array is arranged, a pre-deployment orientation of the seabed horizontal array, sound velocity profile data and position information of a transmitting point; acquiring an array channel response corresponding to the transmitting point; determining a copy array channel response corresponding to the array channel response according to the area position, the pre-deployment orientation, the sound velocity profile data and the position information of the transmitting point; determining a corresponding correlation peak maximum value according to the array channel response and the copy array channel response; and taking the maximum value of the correlation peak as a cost value, and determining an optimal formation parameter of the seabed horizontal array through a preset genetic algorithm.
Owner:NAT UNIV OF DEFENSE TECH
Mechanism entity extraction method, system and device based on multiple training targets
ActiveCN111881692AAvoid error propagationSpeed up extractionSemantic analysisCharacter and pattern recognitionEngineeringEntity model
The invention relates to artificial intelligence, and provides an institution entity extraction method based on multiple training targets, which comprises the following steps: obtaining a training sample set, and carrying out named entity labeling on each training sample in the training sample set; training a preset named entity model by using the labeled training sample set so as to enable the named entity model to reach preset precision; performing sequence labeling on the acquired text information to be detected through the named entity model; and extracting related institution entities inthe to-be-detected text information according to the sequence label. The invention also relates to a blockchain technology. The training sample set is stored in the blockchain. According to the technical scheme provided by the invention, the problems of low efficiency and poor quality of an existing mechanism entity extraction method can be effectively solved.
Owner:PING AN TECH (SHENZHEN) CO LTD
Event extraction method based on multi-task learning
ActiveCN114741473AAvoid decimationAvoid error propagationCharacter and pattern recognitionNeural architecturesFeature extractionEvent trigger
The invention discloses an event extraction method based on multi-task learning, and aims to realize quick and efficient event extraction when the number of texts is huge. According to the technical scheme, firstly, an event extraction system composed of a client, a negative sample database, an event screening module, a feature extraction module, an event classification module, an event trigger word and argument extraction module and an event information integrator is constructed. Then selecting a training set, and training the event extraction system by using the training set to obtain network weight parameters; carrying out event screening on the events by adopting the trained event extraction system, judging whether the events are events of predefined categories, and if so, carrying out feature extraction, event classification, event trigger word and argument extraction and event information integration to obtain an event extraction result; and if not, discarding the current event. By the adoption of the method, information implied in data can be fully mined, classification attributes of multiple fields of texts can be rapidly obtained, and the event extraction accuracy and efficiency are improved.
Owner:NAT UNIV OF DEFENSE TECH
Iterative extraction method for maximum energy of measured signals of offshore structures
ActiveCN110991395BImprove analysis accuracyReduce sensitivityCharacter and pattern recognitionState spaceComputational physics
Owner:OCEAN UNIV OF CHINA
A method and device for precoding in a multi-user mimo system
ActiveCN102710390BSmall amount of calculationHigh speedError prevention/detection by diversity receptionSpatial correlationEngineering
Owner:北京万海云科技有限公司
Voice processing method and device, storage medium and program product
PendingCN114242043AImprove accuracySmall amount of calculationSpeech recognitionEngineeringNetwork model
The invention provides a voice processing method and device, a storage medium and a program product. The method comprises the following steps: determining corresponding feature information of a to-be-processed voice on a plurality of frequency bands; for a sequence formed by the feature information on the plurality of frequency bands, based on a deep learning model used for processing sequence data, obtaining a processing result corresponding to each piece of feature information; and obtaining the processed voice based on the processing result corresponding to each piece of feature information. According to the invention, denoising and dereverberation can be realized at the same time based on the deep learning model, an error transmission phenomenon caused by series connection of different algorithm modules is avoided, the accuracy of the model is improved, in addition, the network model coefficient of each frequency band is shared, the size of the network model and the calculation amount during processing can be effectively reduced, and the processing efficiency is improved.
Owner:DINGTALK (CHINA) INFORMATION TECH CO LTD
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