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32results about How to "Avoid low recognition accuracy" patented technology
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Intelligent flow control system of interactive network and implementing method thereof
InactiveCN102158404AImprove recognition accuracyAvoid low recognition accuracyData switching networksClient-sideIntelligent control system
The invention discloses an intelligent flow control system of an interactive network, comprising client-sides, a router and an intelligent flow control module, wherein the router is communicated with the client-sides by networks, and the intelligent flow control module is arranged on the router. The intelligent flow control system is characterized in that each client-side is provided with an application identification module for carrying out application type identification on the data streams of the client-side. The invention also discloses an implementing method of the intelligent flow control system of the interactive network, comprising the steps as follows: (a) the application identification modules are used for identifying the data streams generated by the client-sides, and transmitting the data streams to the router after program identification codes are stamped on the data streams; and (b) a classification module on the router receives the data streams from each client-side and stores the data streams in a classification mode. Compared with the prior art, by using the system and the method provided by the invention, the identification accuracy of the router for a personal computer (PC) is greatly improved, the problems of network blockage, disconnection, system crash and the like caused by overload of the router can be avoided, and the practical value is very high.
Owner:成都飞鱼星科技股份有限公司
Automatic emotion recognition method based on bimodal signal
ActiveCN110619301AAvoid low recognition accuracyReduce complexityInternal combustion piston enginesAcquiring/recognising facial featuresSupport vector machineTime domain
The invention discloses an automatic emotion recognition method based on a bimodal signal. The method comprises the following steps: cutting and framing video data containing facial expressions and actions, extracting a facial expression picture sequence, extracting LBP-TOP features of the facial expression picture sequence, extracting pulse wave signals of the facial expression picture sequence based on a chromaticity model, and extracting time domain and frequency domain features of the pulse wave signals; fusing the extracted LBP-TOP features of the facial expression picture sequence with the time domain and frequency domain features of the pulse wave signal; dividing the fused facial expression images into a training set and a test set, inputting the training set into a support vectormachine for training and optimization, and then inputting the training set into the support vector machine to realize automatic emotion recognition in the facial expression images. According to the invention, the system complexity is greatly reduced, and the convenience of the system is improved; the fused features can avoid the problem of low recognition precision caused by artificial intentionalemotion masking or no obvious expression change of the human face.
Owner:道和安邦(天津)安防科技有限公司
Modulation mode identification method based on deep learning
ActiveCN110163282AImprove learning effectAvoid low recognition accuracyCharacter and pattern recognitionNeural architecturesSignal-to-noise ratio (imaging)Algorithm
The invention provides a modulation mode identification method based on deep learning, which is used for solving the problem of low identification accuracy in the prior art, and comprises the following implementation steps of: (1) obtaining a training set and a test set; (2) establishing a neural network NNs; (3) dividing the training set into a plurality of sub-training sets based on the signal-to-noise ratio, and respectively training the neural network NNs by using the sub-training sets to obtain a plurality of trained neural networks; and (4) evaluating the signal-to-noise ratio snr of theto-be-tested modulation signal, selecting an applicable trained neural network according to the interval where the snr is located, and identifying the modulation mode of the to-be-tested modulation signal. When the neural network NNs are trained, the internal relation and rule of the sample data and the sample labels of all the sub-training sets can be accurately found, the learning effect of theneural network NNs is enhanced, the recognition accuracy is improved, and meanwhile self-adaptive modulation mode recognition based on the signal-to-noise ratio is achieved. The method can be used inthe fields of modulation mode identification and the like in non-cooperative communication.
Owner:XIDIAN UNIV
Micro-expression recognition method based on deep learning
PendingCN111353390AReduce training timeReduce system complexityNeural architecturesAcquiring/recognising facial featuresIdentification rateExpression - action
The invention discloses a micro-expression recognition method based on deep learning. The micro-expression recognition method comprises the following steps: 1, cutting, framing and extracting video data containing expression actions; 2, performing face alignment, face clipping, normalization and other preprocessing on the extracted expression sequence; 3, performing data enhancement operation on the obtained data set; 4, establishing a neural network model; 5, dividing all facial expression data into a training set and a test set in proportion; and 6, testing the model by using the test set, outputting information such as identification accuracy, identification time, errors and the like, and selecting the current model when the identification rate meets the requirements. The micro-expression recognition method based on deep learning has the advantages of being simple, efficient, low in cost, high in precision and the like.
Owner:道和安邦(天津)安防科技有限公司
Mine slight shock and blasting signal identification method based on waveform slope before and after peak value
ActiveCN104834004AUnaffected by background noiseNot easy to pick upSeismic signal processingAlgorithmPeak value
The invention discloses a mine slight shock and blasting signal identification method based on waveform slope before and after a peak value. The method comprises: step 1, acquiring a linear identification equation: based on N times of slight shock events and M times of blasting events, obtaining a linear identification equation with logarithm of A, logarithm of k1, logarithm of k2, logarithm of k3, logarithm of k4, logarithm of k5, and logarithm of k6 as characteristic parameters, the linear identification equation being Y=a1* lg(k1)+a2*lg(k2)+a3*lg(k3)+a4*lg(k4)+a5*lg(k5)+a6*lg(k6)+b*lg(A)+c; step 2, calculating a distinguishing threshold value Yd; step 3, based on the linear identification equation and the distinguishing threshold value Yd, identifying a to-be-identified event; and calculating a distinguishing value Y of the to-be-identified event, if Y<=Yd, the to-be-identified event being a slight shock event, and if not, the to-be-identified event being a blasting event. The method is low in calculated amount, and identification results are not influenced by signal noise, and the method is high in accuracy.
Owner:CENT SOUTH UNIV
Ocean front area acquisition method and device, computer equipment and storage medium
ActiveCN111860146AIncrease flexibilityImprove timelinessKernel methodsScene recognitionMarine engineeringObservation data
The invention relates to an ocean front area acquisition method and device, computer equipment and a storage medium. The method comprises the following steps: determining a roughly estimated ocean front area, target paths for a plurality of unmanned naval vessels to reach the roughly estimated ocean front area and target duration for the unmanned naval vessels to reach the roughly estimated oceanfront area along the target paths according to acquired satellite remote sensing observation data; determining each initial position of each unmanned ship in the roughly estimated ocean front area according to received arrival confirmation information sent when each unmanned ship reaches the roughly estimated ocean front area; outputting an adjustment instruction according to the region change information of the roughly estimated ocean front region determined by the multiple groups of satellite remote sensing observation data received within the target duration to indicate each unmanned ship to perform adjustment based on the respective corresponding initial position so as to obtain the adjusted position of each unmanned ship; and determining a target ocean front area according to each received adjusted position. By adopting the method, the identification accuracy of the ocean front area in the sea area can be improved.
Owner:SUN YAT SEN UNIV
Trip mode identification method based on GPS trajectory data
ActiveCN107330469AEasy to implementAccurate classificationData processing applicationsCharacter and pattern recognitionTravel modeGps trajectory
The invention discloses a trip mode identification method based on GPS trajectory data. For trip modes lack of a GPS signal and having an incomplete signal, a subway identification method based on a rule is adopted; and, for other trip modes having normal GPS signal records, a random forest classifier is adopted, and modeling and verification are performed through a combination with the GPS trajectory data. Before trip modes are identified, 4 kinds of characteristic parameters related to mode identification are screened through a characteristic selection process, and all the real trip modes can be accurately identified. The method is not limited by the GPS data and not relied on other data sources, and the method has the advantages of high universality, simple calculation and accurate and reliable identification results; and the method is suitable for trip mode identification based on the GPS trajectory data, and is in favor of large-scale promotion of trip survey based on intelligent mobile phones.
Owner:SHANGHAI JIAO TONG UNIV
Method and system for detecting bad appearance of product and storage medium
PendingCN111861990AReduce occupancyAvoid low recognition accuracyImage analysisCharacter and pattern recognitionImaging processingMinimum bounding rectangle
The invention provides a method for detecting the bad appearance of a product, and the method comprises the following steps: obtaining a product appearance image, carrying out the graying of the product appearance image, and obtaining a first gray level image; binarizing the first grayscale image to obtain a second grayscale image; performing contour extraction on the second grayscale image, and screening to obtain a contour combination; obtaining a minimum bounding rectangle of the contour combination, completing appearance feature classification of the product appearance image through a neural network according to the minimum bounding rectangle, and identifying a product with poor appearance according to a classification result. According to the invention, contour extraction is carried out by sequentially carrying out graying and binaryzation, so that the reduction of the recognition accuracy caused by the influence of light is avoided; and by combining the minimum bounding rectangleof the contour combination with the neural network, the occupation of operation resources is reduced, the image processing speed is at a millisecond level, the operation real-time performance is relatively high, the detection effect is relatively good, automatic identification and testing can be realized, and the invention can be widely applied to the technical field of product quality detection.
Owner:宜通世纪物联网研究院(广州)有限公司
Method and apparatus for character string recognition
InactiveUS20080240582A1Avoid low recognition accuracyCharacter recognitionDistortionCharacter recognition
A method and an apparatus for character string recognition may be provided that enables prevention of a decrease in recognition accuracy for a character string even when distortion of an image appears in a direction perpendicular to a medium transfer direction.
Owner:SANKYO SEIKI MFG CO LTD
Recognition model training method, device and equipment and storage medium
PendingCN111612081AAvoid low recognition accuracyImprove recognition accuracyNeural architecturesNeural learning methodsPattern recognitionData set
The invention discloses a recognition model training method, device and equipment and a storage medium, and relates to the field of financial science and technology, and the method comprises the following steps: obtaining a to-be-trained image, and constructing a simulation image according to the to-be-trained image; determining a training data set according to the to-be-trained image and the simulation image; and based on the training data set, training through a generative adversarial network and a recognition network in a preset neural network model to obtain a recognition model. Accordingto the method, the training data set is obtained by constructing the simulation image through the obtained image, and the situation that the recognition accuracy of the recognition model obtained through training is low due to the fact that samples of the training data set are insufficient is avoided, that is, the recognition accuracy of the recognition model obtained through training is improved.
Owner:WEBANK (CHINA)
3D dynamic portrait recognition monitoring device and method
PendingCN112052730ASmall footprintImprove clarityImage enhancementCharacter and pattern recognitionImaging processing3d image
The invention belongs to the technical field of face recognition, and discloses a 3D dynamic portrait recognition monitoring device and method. The system comprises an image acquisition module, an image processing module, a human face feature point pickup module, a 3D human face modeling module, a central processing module, a wireless signal transmission module, a monitoring terminal, a database,a human face recognition and judgment module, a human face search module, a human face image storage module, an image classification module and a display module. According to the invention, the camerais used to obtain the human face image data, and the image is preprocessed, so that the definition of the image is improved, the 3D image recognition of the human face image in subsequent steps is facilitated, and the accuracy is improved; according to the method, the feature points of the human face are extracted through the feature point extraction program, the two-dimensional face image is converted into the 3D human face through the 3D face modeling technology, and the problem that the traditional two-dimensional image recognition precision is low is avoided.
Owner:广州市标准化研究院
Driver behavior recognition method based on multi-source information fusion
InactiveCN114299473AImprove accuracyImprove recognition accuracyCharacter and pattern recognitionNeural architecturesDriver/operatorAlgorithm
The invention provides a driver behavior recognition method based on multi-source information fusion. The driver behavior recognition method is characterized by comprising the steps that 1, images or videos related to driver behaviors recorded in a driving simulator and vehicle motion state data are obtained; step 2, inputting the processed driver behavior data into a fine-tuned Vision Transform first sub-model, and outputting a probability matrix P1 of four driving behavior categories; 3, preprocessing the synchronously recorded vehicle motion state data, inputting the data into the trained Bi-LSTM second sub-model, and outputting a probability matrix P2 of four driving behavior categories; and step 4, calculating the probability output matrixes P1 and P2 obtained in the step 2 and the step 3 to obtain information entropies H1 and H2 of the first sub-model and the second sub-model, and finally performing weighted decision fusion on Softmax function output probability values of different sub-models to realize final classification of the four driving behaviors. According to the invention, a plurality of driving behavior identification tasks are integrated, and the anti-interference performance is high.
Owner:HANGZHOU DIANZI UNIV
Recognition method of mine microseismic and blasting signals based on waveform slope before and after the peak
ActiveCN104834004BUnaffected by background noiseNot easy to pick upSeismic signal processingPeak valueComputer science
Owner:CENT SOUTH UNIV
Pattern recognition method and pattern recognition apparatus
ActiveUS9092662B2Avoid low recognition accuracyIncrease processing costCharacter and pattern recognitionLocal pattern
Owner:CANON KK
Ship trajectory classification method based on feature selection and hyper-parameter optimization
ActiveCN113239025AImprove performanceImprove versatilityCharacter and pattern recognitionGeographical information databasesData cleansingFeature based
The invention discloses a ship trajectory classification method based on feature selection and hyper-parameter optimization. For the problem of unbalanced original data in ship trajectory classification, firstly, data cleaning and preprocessing are performed on multiple pieces of trajectory data of an automatic ship identification system, then all trajectories are drawn by matplotlib, unavailable trajectories are deleted, then features are calculated to obtain additional features, dimensionality reduction processing is performed on speed, course and trajectory coordinates, backward feature selection is carried out on all features after dimension reduction processing through a random forest (RF), finally hyper-parameter optimization is carried out through the random forest, and classification prediction is carried out on the features through model training and performance evaluation without depending on an external information source. The ship trajectory classification method has high performance and is stable, and can be effectively applied to actual ship trajectory classification.
Owner:SICHUAN UNIV
Dialogue intention recognition method and device, electronic equipment and readable storage medium
PendingCN114297359AImprove accuracyAvoid low recognition accuracyNatural language data processingText database queryingLanguage understandingNatural language understanding
The invention provides a dialogue intention recognition method and device, electronic equipment and a readable storage medium. A natural language understanding model is utilized to determine a possibility score of each intention corresponding to a consultation dialogue; if a real intention capable of representing the consultation dialogue does not exist in at least one first intention determined according to the possibility score, determining a target keyword from the consultation dialogue by utilizing a configured business keyword model, and searching at least one second intention matched with the target keyword in a business knowledge graph; and if the at least one second intention does not include the first intention with the highest possibility score, further determining a real intention indicated by the consultation dialogue from the at least one second intention according to the feedback of the user. In this way, the accuracy of user intention recognition can be improved, and the situation that due to the fact that the character generalization ability of a natural language understanding model is insufficient, the recognition accuracy is low, and the intention of the user cannot be recognized is avoided.
Owner:中电金信软件有限公司
Driver intention recognition method considering human-vehicle-road characteristics
ActiveCN113386775AImprove reliabilityImprove accuracyExternal condition input parametersDriver input parametersDriver/operatorIn vehicle
The invention provides a driver intention recognition method considering human-vehicle-road characteristics. The method is characterized by comprising the following steps: step 1, acquiring related data of a vehicle and surrounding vehicles, driver behavior actions and scene information outside a cab recorded in a driving simulator; step 2, preprocessing the data of the vehicle and the surrounding environment acquired from the driving simulator, and inputting the data into a trained GrowNet network to obtain probability values Pi (P1, P2, ..., P5) of five categories; step 3, respectively storing and processing the video data acquired by two cameras to obtain probability values P'i (P'1, P'2, ..., P'5) of five categories finally; and step 4, performing weighted summation on the Pi and the P'i obtained in the step 2 and the step 3, and taking the category corresponding to the maximum value after five categories are summed as the finally identified driving intention. The driving simulator is fully utilized, data can be collected without depending on a vehicle-mounted sensor, and the experiment is more convenient. In addition, not only can offline training be carried out, but also online testing can be carried out, so that the applicability is improved.
Owner:HANGZHOU DIANZI UNIV
Accessory device for array particle collision sensors
ActiveCN111226576AAccurate detectionRealize follow-up detectionMowersParticle collisionCombine harvester
The invention discloses an accessory device for array particle collision sensors. An impurity discharging mouth is formed in the tail of a combine harvester, a mounting rack is sequentially provided with a screen connecting bracket, a funnel connecting bracket, a sensor accessory mounting bracket and a sensor mounting bracket from top to bottom, and the bottom of the mounting rack is hinged to thebottom of the impurity discharging mouth; the angle of the mounting rack can be adjusted and fixed, the positions of a screen and a funnel relative to the impurity discharging mouth can be adjusted,and the sensor accessory mounting bracket is installed on the mounting rack; and the sensor accessory is adjustable, and is vertically corresponding to the outlet of the lower end of the funnel, the sensor mounting bracket is mounted on the mounting rack, and the array particle collision sensors are located directly below the sensor accessory. Through the accessory device, the angle, speed and position of material collision on the particle collision sensors can be adjusted, the problem of low recognition accuracy rate which is caused by random speed and angle of particle collision can be avoided, and meanwhile, occurrence of particle collision in a gap of detection units of the array particle collision sensors can be avoided, so that the detection accuracy of the particle collision sensorsis improved greatly.
Owner:ZHEJIANG UNIV
Mathematical formula symbol identification method
PendingCN111310525AReduce complexityReduce computing costNeural architecturesCharacter recognitionHandwritingAlgorithm
The invention discloses a mathematical formula symbol identification method, which comprises the following steps of: processing and identifying mathematical formula symbols by using an implicit segmentation model according to a mathematical formula to be identified, wherein in the process of processing and identifying the implicit segmentation model, the real-time position judgment result of the direction judgment network on the mathematical formula symbol is used as the input of the implicit segmentation model processing to be processed, and the implicit segmentation model identifies the mathematical formula symbol. And a direction judgment network is added to enhance the encoding and decoding capabilities in a two-dimensional space. By adopting the method, the accuracy of online handwriting, offline handwriting and optical character mathematical formula recognition is greatly improved.
Owner:中财颐和科技发展(北京)有限公司
Method and apparatus for character string recognition
InactiveUS8467608B2Avoid low recognition accuracyCharacter recognitionSensing by electromagnetic radiationPattern recognitionDistortion
Owner:SANKYO SEIKI MFG CO LTD
Recognition method of mine microseismic and blasting signals based on the slope of trend line of waveform onset
ActiveCN104297788BSolve problems that are difficult to automatically identifyEasy to calculateSeismic signal processingTime domainDiscrimination threshold
Owner:CENT SOUTH UNIV
License plate recognition method, device, and equipment and medium
PendingCN112784840AFast recognitionAvoid low recognition accuracyCharacter and pattern recognitionNeural architecturesImage resolutionEngineering
The invention discloses a license plate recognition method, device, and equipment and a medium. The method comprises the steps: acquiring a to-be-recognized license plate image; performing gray processing on the to-be-recognized license plate image to obtain a to-be-recognized gray license plate image; and inputting the to-be-recognized gray license plate image into a license plate recognition model for license plate recognition to obtain a license plate number sequence corresponding to the to-be-recognized gray license plate image. According to a traditional license plate recognition method, characters in a license plate image are segmented by adopting an artificial design algorithm in combination with projection, connection and / or contour extraction and other methods, a single character image is obtained, and then character recognition is performed on the single character image through a classifier, and thus technical problems of low recognition precision and low recognition speed of a subsequent character recognition result caused by the fact that character segmentation quality is easily influenced by factors such as noise, low resolution, blurring or deformation of an input image exist in the prior art are caused. However, with the provided method, the problems in the prior art are solved.
Owner:DONGGUAN ZKTECO ELECTRONICS TECH
Platform monitoring device and system
InactiveCN110139077ARealize intelligent identificationAvoid low recognition accuracyTelevision system detailsColor television detailsOptical ModuleComputer module
The invention provides a platform monitoring device and system. The platform monitoring device comprises a camera body, and an optical module, an inertial measurement unit, a signal processing mainboard and an AI chip module which are arranged in the camera body, the inertial measurement unit obtains attitude information of the camera body and sends the attitude information to the signal processing mainboard; when the signal processing mainboard judges that the position of the camera body is changed according to the attitude information of the camera body, the signal processing mainboard reports to external equipment; the optical module collects a video image of a target on the moon platform and sends the video image to the signal processing mainboard; and the AI chip module calls a presettarget detection algorithm according to the video image sent by the signal processing mainboard, identifies a target, and sends an identification result to the signal processing mainboard. Accordingto the invention, while intelligent identification of various events of the platform is realized, attitude sensing and reporting of the camera can be realized, and reduction of identification precision caused by ROI (Region of Interest) change due to attitude change is avoided.
Owner:HANGZHOU YAMEILIJIA TECH CO LTD
Image processing apparatus
ActiveUS11157755B2Reduce resolutionReduce computing costImage enhancementImage analysisImaging processingNuclear medicine
Owner:TOYOTA JIDOSHA KK +1
Bridge floor multi-axis moving load recognition method based on diagonal relaxation orthogonal projection iterative algorithm
InactiveCN106874583AAvoid low recognition accuracySimple methodGeometric CADDesign optimisation/simulationMobile vehicleMulti axis
The invention discloses a bridge floor multi-axis moving load recognition method based on the diagonal relaxation orthogonal projection iterative algorithm. The method includes the following steps that firstly, m displacement sensors are attached to corresponding positions x1, x2,..., xm on the bottom face of a bridge, and the displacement of a bridge floor multi-axis moving vehicle load fk(t) at the x position at the t moment is v(x,t), wherein k is 1,2,3,..., and k is the number of vehicle axles; secondly, an oscillatory differential equation is established; thirdly, the equation (1) is solved; fourthly, a multi-axis moving load system equation recognized by displacement responses is established for the bridge under the k-axis vehicle load action; fifthly, the precise value of a multi-axis moving load is solved through the diagonal relaxation orthogonal projection iterative algorithm. The multi-axis moving load can be recognized by measuring the bridge displacement responses only, the recognition method is simple, precision is high, feasibility is good, and the method can be widely applied to moving load recognition of various types of bridges.
Owner:NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER
A travel mode identification method based on GPS trajectory data
ActiveCN107330469BEasy to implementAccurate classificationData processing applicationsCharacter and pattern recognitionTravel modeData Origin
The invention discloses a travel mode identification method based on GPS trajectory data. For travel modes with missing or incomplete GPS signals, a rule-based subway identification method is adopted; for other travel modes with normal GPS signal records, a random forest classifier is used , combined with GPS trajectory data for modeling and verification. Before mode identification, the feature selection process screens out 4 types of feature parameters related to mode identification, which can accurately identify all real travel modes. This method is not limited by GPS data, does not rely on other data sources, has high versatility, simple calculation, and accurate and reliable recognition results. It is suitable for travel mode recognition based on GPS trajectory data and is conducive to promoting large-scale promotion of travel surveys based on smartphones. .
Owner:SHANGHAI JIAO TONG UNIV
Image processing apparatus
ActiveUS20200026934A1Reduce the amount of calculationCalculation cost is highImage enhancementImage analysisImaging processingRadiology
An image processing apparatus (12) has a processing device (122) for executing, on a first image (111w) captured by a first imaging device (11w) imaging a first imaging area and a second image (111t) captured by a second imaging device (11t) imaging a second imaging area, an image recognition processing for recognizing a target in the first image and the second image, the processing device executes the image recognition processing on a non-overlapped image part (113w) of the first image without executing it on a overlapped image part (112w) of the first image when the processing device executes the image recognition processing on the first image, the non-overlapped image part includes a non-overlapped area at which the first imaging area does not overlap with the second imaging area, the overlapped image part includes a overlapped area at which the first imaging area overlaps with the second imaging area.
Owner:TOYOTA JIDOSHA KK +1
Intelligent lock fingerprint recognition device capable of prolonging service life
PendingCN110288750AExtended service lifeEnhance touch experienceIndividual entry/exit registersMatching and classificationIdentification deviceEmbedded system
The invention discloses an intelligent lock fingerprint recognition device capable of prolonging the service life. The fingerprint recognition device comprises a fingerprint recognition module and a glass panel, wherein the fingerprint recognition module is provided with a fingerprint acquisition module for reading the resistance change of the skin of a finger of a user. The fingerprint acquisition module is provided with an acquisition panel, and the acquisition panel clings to the bottom surface of the glass panel, wherein the surface of the glass panel is provided with a fingerprint acquisition area for the finger of the user to touch and sense, and the fingerprint acquisition area is opposite to the fingerprint acquisition module. The device can reduce the loss, and the service life is remarkably prolonged.
Owner:广东好太太智能家居有限公司
Three-dimensional object recognition method combining view importance network and self-attention mechanism
PendingCN114550162AEasy to identifyInhibit expressionNeural architecturesNeural learning methodsFeature extractionThree dimensional shape
The invention discloses a three-dimensional object recognition method combining a view importance network and a self-attention mechanism. The method comprises the steps that a three-dimensional object to be recognized is projected from n different visual angles to obtain n different two-dimensional views, and n is larger than or equal to two; performing feature extraction on the n views through a basic CNN model to obtain feature maps of the corresponding views; the importance degrees of the n views for three-dimensional object recognition are judged through a view importance network, the features are enhanced to different degrees according to the importance degrees, and a view enhanced feature map is obtained; processing the view enhanced feature map by using a self-attention mechanism to obtain a three-dimensional shape descriptor; and inputting the three-dimensional shape descriptor into a full-connection network to carry out multi-view object identification so as to realize three-dimensional object identification. According to the method, important views beneficial to three-dimensional object recognition are highlighted, meanwhile, interference of non-important views on three-dimensional object recognition is restrained, and the three-dimensional object recognition accuracy is improved.
Owner:BEIJING UNIV OF TECH
Method and device for identifying table in PDF document
PendingCN114067323AAccurate identificationAvoid low recognition accuracyCharacter and pattern recognitionEngineeringData mining
The invention relates to the field of data processing, and provides a method for identifying a table in a PDF document, which comprises the following steps: acquiring an original target page of the PDF document; when it is recognized that no conventional table exists in the original target page, or when the recognition result of the conventional table in the original target page does not meet a preset condition, recognizing whether a special table exists in the original target page or not through a special table recognition module, and the conventional table referring to a table with crossed lines; the special table being a table without cross lines, and the special table identification module is a module for identifying the table without cross lines. According to the method, the identification accuracy of the table in the PDF document can be improved.
Owner:深圳价值在线信息科技股份有限公司
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