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730results about How to "Meet the needs of practical applications" patented technology

Human body action recognition method and mobile intelligent terminal

The invention discloses a human body action recognition method and a mobile intelligent terminal. The human body action recognition method comprises the steps that human body action data are acquired for training so that feature extraction parameters and template data sequences are obtained, and the data requiring performance of human body action recognition are acquired in one time of human body action recognition so that original data sequences are obtained; feature extraction is performed on the original data sequences by utilizing the feature extraction parameters, and the data dimension of the original data sequences is reduced so that test data sequences after dimension reduction are obtained; and the test data sequences and the template data sequences are matched, and generation of human body actions corresponding to the template data sequences to which the test data sequences are correlated is confirmed when the successfully matched test data sequences exist. Dimension reduction is performed on the test data sequences so that the requirements for the human body action attitudes are reduced, and noise is removed. Then the data after dimension reduction are matched with the templates so that calculation complexity is reduced, accurate human body action recognition is realized and user experience is enhanced.
Owner:GOERTEK INC

Hierarchical landmark identification method integrating global visual characteristics and local visual characteristics

The invention discloses a hierarchical landmark identification method integrating global visual characteristics and local visual characteristics. High-dimensional characteristic vectors of landmark images are obtained and are used as the global visual characteristics of the landmark images; the local visual characteristics of the landmark images are obtained; the global visual characteristics andthe local visual characteristics are stored by adopting a hierarchical tree-shaped structure, and a visual characteristic set is obtained; each image is characterized according to the visual characteristic set; the images are pre-retrieved according to the global visual characteristics xi, and first candidate images are obtained; the first candidate images are further retrieved according to statistical characteristics vi of local outstanding points, and second candidate images are obtained; and the second candidate images are further retrieved according to a characteristic set yi of the localoutstanding points, and final candidate images are obtained and are fed back to a user. By adopting the hierarchical landmark identification method, the images to be identified can be rapidly and accurately retrieved, so the requirement of the user for convenient information acquisition is satisfied; and besides, through removing certain mismatching points, the landmark identification accuracy isimproved and the landmark identification complexity is reduced.
Owner:TIANJIN UNIV

Method for identifying user action and intelligent mobile terminal

The present invention discloses a method for identifying a user action and an intelligent mobile terminal. The method comprises: acquiring user action data, and training the user action data to obtain a feature extraction parameter and a template symbol sequence; collecting data that needs to execute user action identification during user action identification to obtain an original data sequence; performing feature extraction on the original data sequence by using the feature extraction parameter to obtain a dimension-reduced test data sequence; converting the test data sequence into a discrete character string to obtain a symbol sequence of the test data sequence; and performing matching on the symbol sequence of the test data sequence and a template symbol sequence, and when the matching is successful, determining that the user action corresponding to the template symbol sequence occurs. According to the method provided by an embodiment of the present invention, dimension reduction is performed on the original data sequence by using the feature extraction parameter, the dimension-reduced data sequence is symbolized, and then the dimension-reduced data sequence is matched with the template symbol sequence, so that calculation complexity is lowered, perceptual identification efficiency is improved, and good user experience is achieved.
Owner:GOERTEK INC

Enrollment automatic question-answering method and system based on conversation robot

The invention relates to an enrollment automatic question-answering method and system based on a conversation robot. The method comprises the following steps that 1, characters input by a user are obtained; 2, character processing is conducted on the characters input by the user; 3, a best answer is selected from a knowledge base by means of a fuzzy matching method and an internal reasoning mechanism according to the characters subjected to character processing; 4, the best answer is sent to the user. According to the enrollment automatic question-answering method and system based on the conversation robot, the ALICE open-source conversation robot is improved, a domain ontology base serves as an additional knowledge base of a question-answering system, a hypernym-hyponym relation of a constructed domain ontology is utilized for conducting user intention excavation on a problem put forward by the user, a related content recommendation is given to the user by means of hypernym-hyponym information of the domain ontology on the basis of achieving basic question answering, therefore, an examinee can also obtain some recommended results with associated content when the examinee does not obtain an answer of the relevant question, and the satisfaction degree of the question-answering system is improved.
Owner:CAPITAL NORMAL UNIVERSITY +1

Circuit and method for realizing TDI in CMOS image sensor

The invention discloses a circuit and a method for realizing a transport driver interface (TDI) in a complementary metal oxide semiconductor (CMOS) image sensor, and relates to the field of analog integrated circuit designs. The circuit comprises a pixel array, a metal oxide semiconductor (MOS) tube, a sampling capacitor, an operational amplifier, serial buses and an integrator array formed by connecting a plurality of integrators in parallel; each integrator comprises a first switch, a second switch, a third switch, a fourth switch, a fifth switch and an integrating capacitor; the pixel array is respectively connected with one end of the sampling capacitor and the source electrode of the MOS tube through serial buses; the grid electrode of the MOS tube is connected with a bias voltage; the drain electrode of the MOS tube is earthed; the other end of the sampling capacitor is respectively connected with the negative polarity end of the operational amplifier and one end of the first switch; the positive polarity end of the operational amplifier is connected with a reference voltage; the other end of the first switch is respectively connected with one end of the second switch and one end of the fourth switch; the other end of the second switch is respectively connected with one end of the third switch and one end of the fifth switch; the other end of the third switch is connected with the output end of the operational amplifier; the other end of the fourth switch is connected with one end of the integrating capacitor; and the other end of the integrating capacitor is connected with the other end of the fifth switch.
Owner:南通南平电子科技有限公司

Treated sewage quality prediction method based on combination of support vector classification and GRU neural network

The invention discloses a treated sewage quality prediction method based on combination of support vector classification and a GRU neural network, and belongs to the technical field of sewage treatment. Missing value processing, abnormal value elimination and data standardization are carried out on the collected sewage historical data, a PCA principal component analysis method is adopted to carryout dimension reduction on the data, and the selected auxiliary variable is used as an input variable of a sewage quality prediction model; a sewage effluent key prediction model is established by adopting a GRU neural network suitable for processing time series data, a support vector machine model is firstly introduced to classify sewage quality data, and then the classified data is respectivelymodeled through the GRU neural network algorithm to predict effluent quality. When the SVM model is trained, a grid search method and a cross validation method are used for optimizing model parameters, the prediction precision of the obtained joint prediction model is more accurate, the model effect is better, the network performance can meet the actual application requirements, and accurate prediction of the effluent quality of the sewage treatment system can be realized.
Owner:HEFEI UNIV

Rotary speed measuring device and rotary speed measuring method

The invention discloses a rotary speed measuring device and a rotary speed measuring method. The rotary speed measuring device is realized by the following steps: a vibration signal picking sensor is fixedly arranged on a shell of a rotary body to be measured, a supporting seat, a rigid foundation or a rigid object which is in direct contact with the rotary body to be measured and is adjacent to a rotary body; a vibration signal excited by the rotary body to be measured is acquired by the vibration signal picking sensor; the vibration signal is transmitted to a signal analyzing and processing module by a signal transmission lead wire; and the signal analyzing and processing module is used for analyzing and processing the vibration signal so as to extract the rotary speed of the rotary body to be measured. The rotary speed measuring method comprises the steps of: setting a sampling frequency, a data truncation length and a vibration order; carrying out vibration signal picking, filtering, data windowing, data truncation, data conversion, feature data extraction, feature data check, rotary speed calculation, rotary speed check, vibration order check and rotary speed real-time measurement; and according to the vibration order relation, calculating the rotary speed of the rotary body to be measured. The rotary speed measuring device can measure the rotary speed of the rotary body to be measured without directly contacting with the rotary body to be measured; and the measured rotary body does not need an outward extending end, so that the rotary speed measuring device is convenient to use.
Owner:CHINA AUTOMOTIVE TECH & RES CENT

Method for identifying information fulfilling card based on template matching

The invention relates to an information filling card identifying method based on template matching. A blank information card is used to build the image information of a template and obtain a template information card; the effective filling threshold of the filling point option of the template information card is set; the background mode definition of the filling point option of the template information card to be identified is extracted and different background modes of the template option are respectively transferred to carry out filling point identification; if the filling point result is larger than or equal to the set threshold, then the option is considered to be validly filled; or the filling is invalid. The information filling card identifying method based on template matching can be suitable for identifying the gray scale modes of different types; the identifying results are graded and the flexibility is high; the integral identifying rate can be improved; batch identification is available, the human-computer combination can be realized, better meeting the demands of actual application. The information filling card identifying method defines all the option areas to obtain accurate template information. The difference between the current image and the template image are used for identification, thus solving the problem of grain background interference.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI

Chinese word similarity calculation method based on fusion strategy

InactiveCN109960786AImprove the similaritySpearman's correlation coefficient is highNatural language data processingSpecial data processing applicationsSpearman's rank correlation coefficientPattern recognition
The invention relates to a Chinese word similarity calculation method based on a fusion strategy. The method comprises steps of calculating word similarity based on the combination of four of HowNet,synonym forest, Word2Vec trained Chinese Wikipedia encyclopedia corpus and a Baidu dictionary; for two input words, firstly, judging whether the synonyms exist in a HowNet or synonym forest or not; ifyes, using the HowNet or synonym forest for calculating the similarity, if not, judging whether the HowNet or synonym forest exists in the Wikipedia corpus or the Baidu dictionary or not, and if yes,using the Word2vec or the Baidu dictionary for calculating the similarity of the words. The invention provides a Chinese word similarity calculation method based on a fusion strategy. According to the fusion strategy, the known network, the synonym forest, the word2vec and the Baidu dictionary are comprehensively considered, advantage complementation among strategies is formed, the calculated Spearman correlation coefficient and Pearson correlation coefficient are higher than those of other methods, the accuracy of a word similarity calculation result is improved, and the requirements of practical application can be well met.
Owner:BEIJING INFORMATION SCI & TECH UNIV

Chinese patent text similarity calculation method

InactiveCN108549634ASpeed ​​up the reviewHigh accuracy and recallSemantic analysisCharacter and pattern recognitionWeight valueSentence similarity
The invention relates to a Chinese patent text similarity calculation method. The method comprises the steps of performing word segmentation on texts; calculating TF-IDF values for word segmentation results, extracting the word segmentation results with the relatively high TF-IDF values to serve as keywords, locating sentences where the keywords are located to serve as key sentences, and taking maximum weight values of the keywords in the key sentences as weight values of the key sentences, thereby obtaining a keyword set of each text; and calculating weights of comparison texts of the key sentences, selecting the key sentences of the to-be-compared texts and the comparison texts in sequence, and based on the sentence similarity of the key sentences, calculating the similarity of the texts. By utilizing existing patent domain ontologies, semantic relationships in the patent texts are analyzed; by utilizing a vector space model and the domain ontologies, patent text similarity is calculated; the correct rate and the recall rate of a calculation result are relatively high; the similarity between patents can be described more accurately; the patent examination speed can be increased;and the need of actual application can be well met.
Owner:BEIJING INFORMATION SCI & TECH UNIV +1

A pipeline video defect detection method based on a convolutional neural network

InactiveCN109559302AImprove accuracyImprove automated detection efficiencyImage enhancementImage analysisClassification resultCable television
The invention relates to a pipeline video defect detection method based on a convolutional neural network. The method comprises the steps of extracting frames of a video, training a plurality of CNNsto classify each frame of image; counting the result returned by each CNN, determining the defect type of the frame, segmenting the video into continuous image frames by taking the pipeline closed circuit television video as input, and sending each frame of image into a plurality of trained CNNNs for binary classification, wherein the classification result only comprises a certain specific defectand no defect. According to the invention, the accuracy of pipeline defect detection is obviously improved; a feasible method is provided for video detection; the automatic detection efficiency of thepipeline defects can be improved; the pipeline defect detection method has the advantages that the detection accuracy is high, the detection speed is high, the application value in pipeline video defect detection is high, a satisfactory result is obtained, and the pipeline defect detection method can be used as a technical reference for pipeline defect detection workers and can well meet the requirements of practical application.
Owner:NEW TECH APPL INST BEIJING CITY +1

Earthquake collapse analysis method for high-rise steel frame structure

The invention discloses an earthquake collapse analysis method for a high-rise steel frame structure, which comprises the following steps: obtaining the dynamic equation of the high-rise steel frame structure under the earthquake action; according to a central difference method and the dynamic equation, solving the speed and the acceleration of the displacement differential of the high-rise steel frame structure within time interval delta t; according to the Von Mises yield condition and a corrected K&K model, obtaining unit stress sigma t at the t time; defining a failure criterion corresponding to the K&K model; according to the failure criterion, judging whether a unit fails or not; if so, deleting the failed unit; if not, according to a geometric equation and the displacement u(t+delta t) of the high-rise steel frame structure, obtaining the strain increment d epsilon of the unit; according to a damage evolution equation, obtaining the accumulated damage value D of the unit; according to the accumulated damage value D of the unit, calculating the layer damage value of the high-rise steel frame structure; obtaining the stress sigma t+delta t of the t+delta t time unit; and updating time t to t+delta t. According to the earthquake collapse analysis method, the whole collapse damage process of the high-rise steel frame structure under the earthquake action by considering the damage accumulation effect can be precisely simulated.
Owner:扬中市冠捷科创有限公司
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