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278results about How to "Solving recognition problems" patented technology
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Pedestrian re-identification method based on multi-attribute and multi-strategy fusion learning
ActiveCN107330396ARobustShorten the timeBiometric pattern recognitionNeural learning methodsImage extractionTraining phase
The invention discloses a pedestrian re-identification method based on multi-attribute and multi-strategy fusion learning. The method of the invention includes the steps of in an offline training phase, firstly selecting pedestrian attributes which are easy to be judged and have a sufficient distinguishing degree, training a pedestrian attribute identifier on an attribute data set, then labeling attribute tags for a pedestrian re-identification data set by using the attribute identifier, and next, by combining the attributes and pedestrian identity tags, training a pedestrian re-identification model by using a strategy fused with pedestrian classification and novel constraint comparison verification; and in an online query phase, extracting features of a query image and images in a database by using the pedestrian re-identification model, and calculating the Euclidean distance between the feature of the query image and the feature of each image in the database to obtain the image with the shortest distance, which is considered as the result of pedestrian re-identification. In terms of performance, the features in the invention are distinguishable and high accuracy is obtained; and in terms of efficiency, the method of the invention can quickly search for the pedestrian indicated by the query image from the pedestrian image database.
Owner:HUAZHONG UNIV OF SCI & TECH
Method for accurately recognizing high speed mobile vehicle mark based on video
InactiveCN101196980AClear video imageAccurate captureCharacter and pattern recognitionVehicle detectionVideo image
An accurate high-speed moving vehicle mark identification method based on video belongs to a calculation processing method adopting image and mode identification technology to realize vehicle detection and vehicle mark identification. The present invention mainly comprises five function modules, namely a video camera control module, a motion detection module, a vehicle snapshot module, a vehicle positioning module and a vehicle identification module. The present invention acquires a real-time video image through a camera system, judges whether a vehicle passes by processing the video image, judges the motion direction of the vehicle according to motion characteristics, segments a picture of the moving vehicle from an image sequence, positions a vehicle mark through vehicle texture features, and performs classification identification to a vehicle head mark or a vehicle back mark by utilizing vehicle mark features before and after. The present invention can solve the vehicle model and vehicle mark identification of high-speed running vehicles, especially the identification of vehicle back marks.
Owner:WISESOFT CO LTD +1
Method and system for news event extraction based on neural network
InactiveCN107239445ADisambiguationAvoid ambiguitySemantic analysisSpecial data processing applicationsNerve networkSemantic feature
The invention discloses a method and system for news event extraction based on neural network. The method comprises the steps of: conducting data pre-processing on original text of training corpus; introducing an event sentence sequence represented by a word vector into a bidirectional long and short memory network, using the bidirectional long and short memory network to train and obtain semantic features of each candidate trigger word; introducing the event sentence sequence represented by a word vector into a convolutional neural network, using the convolutional neural network to train and obtain global features of the event sentences where the candidate trigger words are in; according to the semantic features of candidate trigger words and the global features of the event sentences where the candidate trigger words are in, using softmax as a classifier to classify each candidate trigger word, and therefore finding out the trigger words for news events, and according to the trigger word type, judging the type of the event. The method and system can quickly and accurately extract news events and deal with news events contained in non-standard statements, and has the advantages of high efficiency and universal applicability.
Owner:CHINA UNIV OF MINING & TECH
Intelligent protocol parsing method and device
InactiveCN101035111AImprove accuracyHigh protocol recognition efficiencyData switching networksNetworking protocolWeb protocols
The invention relates to smart agreement analytical methods and devices used for intruding detection defense (IDS / IPS) and audit products. The purpose of the invention is to provide an agreement not to rely solely on the static ports and matching agreement characteristics of intelligent field protocol analysis technology and analytical format of the agreement is automatically adjusted in different versions of the software and gives accurate results, which enhanced the accuracy of the analysis of the agreement. The invention consists of three major steps: the establishment of agreements features model; agreement recognition; intelligent analysis of that agreement. This invention solved the traditional IDS / IPS products for the non-standard ports or did not have static characteristics of field data packet network protocol identification of problems but for some applications or different versions of the agreement, such as the reasons for the analytical results can provide automated error rectification work.
Owner:BEIJING VENUS INFORMATION TECH
Method and system for network protocol recognition based on tri-classifier cooperative training learning
ActiveCN104270392AImprove recognition accuracyImprove recallTransmissionTraffic capacityNetworking protocol
The invention relates to a method and a system for network protocol recognition based on tri-classifier cooperative training learning. The method comprises the following steps: carrying out IP (Internet Protocol) regrouping and TCP (Transmission Control Protocol) traffic reduction on network original traffic, and stipulating the unit of network data from original packets to flow; extracting each message of unidirectional flow feature information and vectoring to build a feature matrix; building a tri-classifier cooperative training classifier with few identified samples; judging whether a classifying model of an analyzed protocol exists or not, and utilizing a tri-classifier cooperative training learning method to build a protocol classifier if the classifying model does not exist, otherwise, judging the protocol attributes of data packets; training by a tri-classifier cooperative training learning algorithm based on J48 and obtaining the classifying model of the analyzed protocol; carrying out protocol type judgment on network data packets not identified, and outputting two classes of results: one class refers to the network data packets belonging to the target protocol, and the other class refers to network data packets not belonging to the target protocol. High recognition accuracy and high recalling rate are ensured by the method.
Owner:INST OF INFORMATION ENG CHINESE ACAD OF SCI
Distributed vision computing method based on open type Web Service framework
InactiveCN102222213AFlexible arrangements for online upgradesLow costCharacter and pattern recognitionTelevision systemsFeature extractionData center
The invention relates to a distributed vision computing method based on an open type Web Service framework. The method has the technical scheme of: collecting the video image of an identified target by adopting an embedded video collecting front end, and sending the video image back to a data center through network multicast; a computing server is controlled by a control server in the data centerto accomplish the computing task, and carrying out the uncompressing, target detecting, image preprocessing, feature extraction, identification, classification and result drawing of video data; and integrating the computing results. The method solves the defect of difficult compatibility with other systems. Under the uniform scheduling of the control server, the method avoids a great deal of unnecessary matching calculation, improves the performance of system operation, achieves the compatibility with most of databases and simply updated external systems, and realizes the identification and calculation of large-scale databases by adopting a packet mode.
Owner:郑文明
Image characteristic extracting method and device
InactiveCN101493892AEliminate recognition problemsEliminate segmentation problemsCharacter and pattern recognitionLab color spaceFeature extraction
The embodiment of the invention discloses an image feature extraction method and a device thereof, wherein, the image feature extraction method comprises the steps as follows: a weighted image is generated according to a collected image and a pixel of the weighted image is obtained from weighting the sum-difference ratio of a corresponding pixel of the pixel of the weighted image in a RGB color space and the gray value of a corresponding pixel in a Lab color space; a binary image is generated according to the weighted image and comprises a target image and a background image; a hole of the target image in the binary image is filled and noise in the binary image is also removed; edge images of the target image after filling and contour-rectangle images of the edge images are both obtained; and as to any contour-rectangle image, the center and radius of a corresponding circle is obtained according to the calculation of the edge image in the contour-rectangle image. The image feature extraction method and the device thereof proposed solve problems in the recognition of a target-segmented image when targets are more, overlapped with each other and blocked, and are characterized by accurateness and high speed.
Owner:CHINA AGRI UNIV
Recognition and counting method for cells
ActiveCN106056118AImprove recognition rateReduce the effects of image noiseRecognition of medical/anatomical patternsSplit linesChamfer distance
The invention discloses a recognition and counting method for cells, comprising nine steps: preprocessing an image in a micron-order microscopic acquisition environment; extracting cell holes from the preprocessed image; performing closed hole filling of cells by using the knowledge of a connected domain; extracting a contour point sequence of cells from the image filled in step 3; filling non-closed holes of cells by adopting a non-closed hole filling method based on circularity determination; performing chamfer distance transformation on the filled image; performing extreme value uniqueness marking on cell hole positions; segmenting the image after extreme value uniqueness by using a marked watershed method; and quantifying and marking the segmented result. The method has the advantages that the influence of image noise can be greatly reduced, the phenomena of over-segmentation and discontinuous segment lines are eliminated, the segmentation effect is improved, and the cell recognition rate is improved.
Owner:HEFEI UNIV OF TECH
Entity relationship joint extraction method
PendingCN110781683ASolving recognition problemsImprove extraction efficiencyNatural language data processingNeural architecturesMedicineUnstructured data
The invention discloses an entity relationship joint extraction method based on multi-label labeling and a composite attention mechanism, which comprises the following steps: collecting corpus data for research, then removing sentences of which the relationship labels are 'None', and performing multi-label labeling on the rest sentences to form a training set; inputting the sentences subjected tomulti-label labeling into a joint extraction model, identifying entities contained in the sentences and relationships among the entities through the joint extraction model, and constructing a triple;and correcting the extracted triples by utilizing a relationship alignment model so as to adapt to multi-label labeling of (head entity E1 and tail entity E2) entity pairs. The method has the advantages that the accuracy of triple extraction can be effectively improved, and the method is an effective tool for information extraction of unstructured data.
Owner:HOHAI UNIV
Complex image and text sequence identification method based on CNN-RNN
InactiveCN105678293AImprove accuracySolving recognition problemsCharacter and pattern recognitionNeural architecturesText recognitionFeature extraction
The invention relates to the image and text identification field, and specifically relates to a complex image and text sequence identification method based on CNN-RNN. The complex image and text sequence identification method includes the steps: utilizing a sliding sampling box to perform sliding sampling on an image and text sequence to be identified; extracting the characteristics from the sub images obtained through sampling by means of a CNN and outputting the characteristics to an RNN, wherein the RNN successively identifies the front part of each character, the back part of each character, numbers, letters, punctuation, or blank according to the input signal; and successively recording and integrating the identification results for the RNN at each moment and acquiring the complete identification result, wherein the input signal for each moment for the RNN also includes the output signal of a recursion neural network for the last moment and the vector data converted from the recursion neural network identification result for the last moment. The complex image and text sequence identification method based on CNN-RNN can overcome the cutting problem of a complex image and text sequence and the problem that the identification result relies on a language model, thus significantly improving the identification efficiency and accuracy for images and text.
Owner:成都数联铭品科技有限公司
Recurrent neural network-based complex image character sequence recognition system
InactiveCN105654130AImprove accuracySolving recognition problemsCharacter and pattern recognitionNeural learning methodsChinese charactersRecognition system
The present invention belongs to the image character recognition field and relates to a recurrent neural network-based complex image character sequence recognition system. The system includes an image character input module, a slide sampling module, a CNN and an RNN, wherein the image character input module is a scanner, a digital camera or an image character storage module. The slide sampling module in the system performs sliding sampling on an image character sequence to be recognized and inputs sampled sub pictures into the CNN; the CNN extracts features and outputs the features to the RNN; and the RNN recognizes the front part of a Chinese character, the back part of a Chinese character, numbers, letters or punctuations according to the input signals of the CNN, the output data of the CNN at the last time point, and vector data converted from the recognition result of the CNN at the last time point. With the system of the invention adopted, problems in the segmentation of a complex image character sequence can be solved, a language model is not required to be constructed additionally, and the recognition efficiency and accuracy of the complex image character sequence can be significantly improved.
Owner:成都数联铭品科技有限公司
Unknown network protocol identification method and system
ActiveCN103297427AAccurate identificationSolving recognition problemsTransmissionFeature vectorSupport vector machine
The invention relates to an unknown network protocol identification method. The method includes the steps: firstly, taking network data packets as input, and representing each network data packet as a characteristic vector which can be used for classification; secondly, taking the obtained characteristic vectors as input to form a characteristic vector data set, and using a support vector machine oriented active learning method for learning the characteristic vector data set to obtain a classifier aiming at a to-be-tested network protocol; and thirdly, using the obtained classifier to discriminate protocol attributes of to-be-identified network data packets. The invention further provides an unknown network protocol identification system which comprises a data packet modeling module, a classifier construction module and an identification module. The active learning method is adopted, few tagged samples can be used for achieving excellent learning efficiency, and accordingly, the number of the tagged samples in the learning process is reduced effectively, and analyzed network protocols can be identified accurately from miscellaneous network flows.
Owner:INST OF INFORMATION ENG CHINESE ACAD OF SCI
Complex optical text sequence identification system based on convolution and recurrent neural network
InactiveCN105678292AImprove accuracyComplete recognition resultCharacter and pattern recognitionNeural architecturesPattern recognitionChinese characters
Owner:成都数联铭品科技有限公司
Hierarchical cooperated network virus and malice code recognition method
InactiveCN1625121ASolving recognition problemsGood anomaly detectionData switching networksBiological immune systemApplication programming interface
A layered coordinate network virus and vicious code recognizing method. The characteristics are: use strong self-protection mechanism of biological immunity for reference, correspond the network virus and vicious code recognizing method to the multi-level protective mechanism of biological immunity system, judge the dangerous degree of the stand-by detected script through statistically analyzing the word frequency of the key words, based on the point view of 'self-collection' of register form operation analyze and judge the exceptional behavior of the register form written in the form route, and recognize non-self the executing sequence of the programming interface of the applied program, at last send all the exceptional behavior information to the network control station through the network. It well solves the problem of the identification of the unknown network virus and vicious code, and has good capacity of identification, realizes the monitoring and management of the network virus and vicious code of single system and the whole sub-network.
Owner:UNIV OF SCI & TECH OF CHINA
Voice recognition method and device
ActiveCN105118508AImprove user experienceSolving recognition problemsSpeech recognitionComputer hardwareSpeech identification
The present invention provides a voice recognition method and device. The voice recognition method comprises the following steps: a voice command is received by a mobile terminal, and the intensity of a first network signal of the mobile terminal is obtained; when the intensity of the first network signal is not less than a preset threshold, the voice command is sent by the mobile terminal to a cloud server, and the intensity of a second network signal of the mobile terminal is obtained; when the intensity of the second network signal is less than the preset threshold, the voice command is compared with the voice command prestored in the mobile terminal through the mobile terminal to determine whether the voice command is matched with the voice command prestored in the mobile terminal or not; and if the voice command is matched with the voice command prestored in the mobile terminal, a first voice recognition result may be outputted by the mobile terminal according to the prestored voice command. According to the voice recognition method in the embodiment of the invention, the user voice command may be quickly and accurately recognized by the mobile terminal at any network state.
Owner:BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
Mobile terminal equipment auto-identification and value-added service access system
InactiveCN1516514ASolving recognition problemsSolve inputUser identity/authority verificationSpecial service for subscribersTerminal equipmentNetwork communication
Owner:HANGZHOU EASYCOMM TECH
Independent learning based peer-to-peer (P2P) network flow identification method
ActiveCN103312565ASolve the problem of low recognition rate and low accuracySolving recognition problemsData switching networksLearning basedInternet traffic
An independent learning based P2P network flow identification method is an efficient and accurate P2P flow identification method, and a deep packet inspection (DPI) method and a deep flow inspection (DFI) method as well as P2P flow identified by the DPI are used for verifying machine learning based DFI identification results to achieve automatic learning. The problems that DFI cannot be adjusted automatically and the identification rate is low are solved. According to the P2P network flow identification method with the independent learning capacity, the P2P flow is extracted through a Net Filter technology, the DPI technology is used for identification, recognized P2P flow characteristics are added in an internet protocol (IP) address list, and the machine learning based DFI identification results are verified, so that the whole identification process forms a closed-loop system.
Owner:INST OF BIG DATA RES AT YANCHENG OF NANJING UNIV OF POSTS & TELECOMM
Image character recognition method and system based on deep learning and medium
PendingCN112016547ASolving recognition problemsAccurate text recognitionNeural architecturesCharacter recognitionText recognitionEngineering
The invention provides an image character recognition method and system based on deep learning and a medium. The method comprises the steps that the source category of an image is judged; extracting an image target area through a convolutional neural network and classifying the target area; carrying out orientation correction on the image of the target area, rotating the image to a forward orientation, and calculating an inclination angle of the image through line segment detection and a frequency domain signal analysis method; calculating a feature map of the image by using a target detectionalgorithm and a deep convolutional network, and carrying out target segmentation on the text line to carry out character recognition; according to a CRNN algorithm, combining the deep convolutional network with a bidirectional cyclic network, and carrying out end-to-end network training; and obtaining the position of the character in the picture and the model recognition content through training,and extracting character information. By adopting the computer vision and character recognition technology, the recognition problem of bill cards and table document data in the intelligent auditing process in the financial field is solved.
Owner:上海天壤智能科技有限公司
Form recognition method and device in image, electronic equipment and storage medium
ActiveCN111814722AGood effectHigh precisionCharacter and pattern recognitionNeural architecturesText recognitionEngineering
The invention provides a form recognition method and device in an image, electronic equipment and a storage medium. The form recognition method comprises the steps of obtaining a to-be-recognized image; performing cascade correction based on deep learning and straight line detection; performing form area detection based on deep learning; detecting row and column table lines from the form area image, and reconstructing a table structure; recognizing texts in the cells based on a text recognition model of deep learning; realizing identification result formatted output. Through the design, the identification problem of various different types of forms such as a full-frame-line form, a partial-frame-line form and a frameless-line form is solved at the same time, and the form structure and content identification accuracy is improved.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Motion data monitoring method and system
InactiveCN108096807ASolve the dynamic impact forceAvoid measuringCombat sportsMobile phoneMotion sensors
The invention provides a motion data monitoring method and system. A first sensor and a second sensor are used for acquiring motion data, data pictorialization and 2D image 3D synthesis are used, hitting power is measured indirectly through a motion sensor, and learning, training, sparring, feature extraction and strength and weakness countermeasures are supported, so that automatic user identification, automatic motion identification, strong event identification, weak event identification, automatic judgment and formation of automatic match odds are achieved. Besides, the functions of roll calling, sign-up, notification, positioning, alarming and the like can be achieved. The system comprises the sensors, a micro base station, an intelligent mobile phone APP, a PC, a cloud center and other hardware, cloud center software and application software.
Owner:丁贤根
Mutual conversion method of visible light and near-infrared human face images
InactiveCN104700087ASolving recognition problemsEnhance detailsCharacter and pattern recognitionSparse learningPhoto conversion
The invention discloses a mutual conversion method of visible light and near-infrared human face images. The method comprises the steps of converting a near-infrared human face image or a visible light human face photo into an initial visible light human face photo or an initial near-infrared human face image by use of a method based on sparse learning, and converting the initial visible light human face photo or the initial near-infrared human face image into a high-definition detail photo of the visible light human face photo or the near-infrared human face image by use of a method based on multi-characteristic selection. According to the mutual conversion method, heterogeneous human face images are fitted in a stratified manner by use of a method based on sparse regularization and the visible light human face photo is generated from the near-infrared human face image, and therefore, the detail information of the synthetic photo is increased and the problem of heterogeneous human face recognition is solved.
Owner:SHANGHAI JIAO TONG UNIV
A vehicle type recognition method based on a multi-feature fusion neural network and a processing terminal
ActiveCN109359666ASolving recognition problemsImprove accuracyCharacter and pattern recognitionNeural architecturesObject detectionClassification result
The invention relates to a vehicle type identification method based on a multi-feature fusion neural network and a processing terminal. The method comprises the following steps: 1, training a preset neural network by using a training algorithm to obtain parameters of the neural network so as to determine the trained neural network; 2, obtaining an original image including vehicle type feature, preprocessing that original image to obtain a first image consistent with a preset pixel size, and extracting local features from the original image by adopting an object detection algorithm to obtain asecond image including the local features; 3, taking that first image as the data layer of the network, inputting the second image as the rois of the region of interest of the network to the trained neural network for feature extraction, obtaining fusion feature, classifying the fusion features by using a classification algorithm, and obtaining a classification result of a vehicle type and a probability of a corresponding vehicle type. The invention can effectively solve the problem of identifying similar vehicle types and improve the accuracy of vehicle type identification.
Owner:PCI TECH GRP CO LTD
SAR?target variant recognition?method based on multi-information joint dynamic sparse representation
ActiveCN103824088ASolving recognition problemsEasy to judgeCharacter and pattern recognitionTest sampleEuclidean vector
The invention discloses an SAR?target variant recognition?method based on multi-information joint dynamic sparse representation. The method comprises steps: (1) a target training?dictionary with respect to?image?domain target amplitude?information represented by the formula, a shadow?training dictionary with respect to?image?domain target shadow?information represented by the formula and a?frequency domain training dictionary with respect to?frequency domain target amplitude?information represented by the formula are built with an original SAR image of a training sample as the basis, and a multi-information training dictionary D is jointed; (2) a normalized test?target vector shown in the description, a normalized test?shadow vector shown in the description and a normalized frequency domain test?target vector shown in the description are built with an SAR image of a test sample as the basis, and a multi-information test matrix Y shown in the description is obtained after jointing; (3) according to the multi-information training dictionary D and the multi-information test matrix Y, a joint sparse formula is built and a joint sparse coefficient matrix X is solved; and (4) the test sample is restructured by using the obtained joint sparse coefficient matrix X and the final classification result is obtained according to the reconstruction error?minimization principle.
Owner:XIDIAN UNIV
Self-adaptive stair-climbing control system and method
ActiveCN107943021AImprove adaptabilityImprove intelligencePosition/course control in two dimensionsVehiclesSelf adaptiveStairs climbed
The invention discloses a self-adaptive stair-climbing control system and a self-adaptive stair-climbing control method. The self-adaptive stair-climbing control method comprises the steps of: establishing an exoskeleton or biped robot model according to lengths and overall weight of joints and connecting rods; acquiring obstacle distance information, and detecting whether an obstacle exists in the front is detected by means of an obstacle detection module; if so, detecting size information of the obstacle, and judging whether the obstacle is an obstacle that can be crossed by means of an obstacle classification module; if the obstacle is an obstacle that cannot be crossed, controlling a robot to move into a safety range through planning a motion trajectory by means of a safety judgment module; and if the obstacle is an obstacle that can be crossed, completing the crossing of the obstacle by means of the stair-climbing control module. The self-adaptive stair-climbing control system andthe self-adaptive stair-climbing control method solve the problem of identifying environments with unfixed height of stairs, improve the adaptability of the robot to the external environment, realizethe anthropomorphic gait of the robot, improve the overall intelligence of a machine, and have high transportability and stability.
Owner:布法罗机器人科技(成都)有限公司
Complex image and text sequence identification method
InactiveCN105678300AImprove accuracyImprove recognition efficiencyCharacter and pattern recognitionFeature extractionChinese characters
The invention relates to the image and text identification field, and specifically relates to a complex image and text sequence identification method. The complex image and text sequence identification method includes the steps: utilizing a sliding sampling box to perform sliding sampling on an image and text sequence to be identified; extracting the characteristics from the sub images obtained through sampling by means of a CNN and outputting the characteristics to an RNN, wherein the RNN successively identifies the front part of each character, the back part of each character, numbers, letters, punctuation, or blank according to the input signal; and successively recording and integrating the identification results for the RNN at each moment and acquiring the complete identification result, wherein the input signal for each moment for the RNN also includes the output signal of a recursion neural network for the last moment. The complex image and text sequence identification method can overcome the cutting problem of a complex image and text sequence, and can significantly improve the identification efficiency and accuracy for images and text.
Owner:成都数联铭品科技有限公司
Cross-platform user identification method and cross-platform user identification system
InactiveCN104317784ASolving recognition problemsSpecial data processing applicationsPersonalizationFeature extraction
The invention discloses a cross-platform user identification method and a cross-platform user identification system, which take the importance of use messages in social platforms into full consideration and identify whether a user is the same user according to the similarity of personalized information, such as user knowledge, interests, preferences, writing styles and wording habits, reflected by the user messages in two accounts of different platforms within a corresponding period of time. Specifically, the method comprises the steps that obtains message contents, which are released within a preset period of time, in the two accounts of the different platforms are obtained, word segmentation and feature extraction treatment are carried out on the message contents of the two accounts, and on the basis, by utilizing the similarity between the segmented word features of the messages of the two accounts, whether the two accounts of the different platforms belong to the same user is identified. Thus, the cross-platform user identification method and the cross-platform user identification system solve the problem of how to identify the same user on different social platforms, and further provide support for the analysis of cross-platform data of the same user.
Owner:SUZHOU UNIV
Radio frequency and video double-base recognition and comparison integrated machine
InactiveCN103927881ASolving recognition problemsTelevision system detailsRoad vehicles traffic controlPattern recognitionRadio frequency
The invention relates to a radio frequency and video double-base recognition and comparison integrated machine. The radio frequency and video double-base recognition and comparison integrated machine is characterized in that recognition functions of a traffic ultra-high frequency RFID reader-writer and recognition functions of a traffic video recognizing camera are combined, the traffic ultra-high frequency RFID reader-writer and the traffic video recognizing camera are packaged in a traditional traffic camera protection cover to carry out the front end collecting and comprehensive comparing on the vehicle automobile electronic identification (or an electronic license plate) number and a vehicle license ( an iron sheet license plate) number, and data and comparison results are generated. The radio frequency and video double-base recognition and comparison integrated machine comprises the camera protection cover, the video recognizing camera, the RFID reader-writer, a double-base signal processing and comparing module, related accessories and an interface unit. The radio frequency and video double-base recognition and comparison integrated machine can thoroughly solve the problem of fake clone license plate recognition and can achieve other functions of an electronic license plate system and the traffic camera.
Owner:JIANGSU BELLON TECH
A document desensitization system and method based on big data
InactiveCN109284631ASolving recognition problemsTroubleshooting desensitizationDigital data protectionFile access structuresSystems managementData source
A document desensitization system based on big data is used to desensitize Word, Excel, PPT, TXT, PDF, XML format documents desensitization processing, the system is mainly composed of system management module, data source management module, sensitive data discovery module, desensitization task management module, desensitization configuration management module, desensitization verification module,multi-level management module, security audit module seven modules. By means of natural language processing and semantic analysis, the invention solves the identification problem of sensitive data ina document, and the identification accuracy is high. The invention provides a method for solving static desensitization and dynamic desensitization of unstructured data such as documents, which ensures the safety of sharing and exchanging documents under the environment of big data. By analyzing the document, identifying the sensitive data in the document and desensitizing the document, the invention ensures that the original format of the document is not destroyed, and effectively solves the difficulty of desensitizing the document.
Owner:CHINA ELECTRONICS TECH CYBER SECURITY CO LTD
Television station logo identification system based on deep learning
InactiveCN106599892AImprove real-time performanceSolving recognition problemsCharacter and pattern recognitionTelecommunicationsSample collection
The invention relates to a computer vision technology, and discloses a television station logo identification system based on deep learning to improve the ability of station logo identification. The system comprises a sample collection module used for collecting station logo samples, a sample screening module used for screening samples to remove inappropriate samples, a station logo segmentation module used for segmenting a station logo from a background, a sample synthesis module used for artificially synthesizing different samples, a model training module used for training a station logo identification model based on the collected samples and the artificially synthesized samples, and a station logo identification module used for identifying station logos based on the identification model. The system of the invention is suitable for identifying normal station logos, rebroadcast station logos and extremely similar station logos.
Owner:SICHUAN CHANGHONG ELECTRIC CO LTD
Iris identification method based on multidirectional Gabor and Adaboost
ActiveCN102521575ASolving recognition problemsReduce the impact of noiseAcquiring/recognising eyesFeature vectorFeature extraction
The invention relates to an iris identification method based on multidirectional Gabor and Adaboost. The method comprises the following steps that: (1), block division is carried out on a normalized iris image and two-dimensional Gabor characteristics are extract to carry out coding; and a Hanmming distance between corresponding blocks is calculated; and (2), an Adaboost algorithm is used to carry out classification and identification on the block Hanmming distance obtained in the step (1). More particularly, in the characteristic extraction process, Gabor wavelets of eight directions under a same scale are employed; and block division is carried out on the expanded iris image; Gabor characteristics of the whole iris image and submodules of the iris image are simultaneously extracted by combining integral and local information of the iris and then coding is carried out; the whole and local combination is carried out to form a multi-dimensional characteristic vector; the Adaboost algorithm is introduced to carry out characteristic selection; and a classifier is constructed to carry out identification. According to the invention, beneficial effects of the method are as follows: a noise influence is reduced; an identification problem of a low quality iris image can be solved; and the identification performance is good.
Owner:BEIJING TECHSHINO TECH
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