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319 results about "Sample vector" patented technology
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Rank-order equalization
For digital data transmitted using a vector signaling encoding, a rank-order equalizer cancels various channel noise such as inter-symbol interference. Further, rank-order units may be cascaded to achieve improved equalization over successive sample vector signals in a rank-order equalizer. Multiple rank-order equalizers further operate in parallel in a feed forward mode or in series in a feedback mode to provide a continuous vector signaling stream equalization.
Owner:KANDOU LABS
Building systems for tracking facial features across individuals and groups
ActiveUS9111134B1Improve accuracyIncrease percentageAcquiring/recognising facial featuresVideo sequenceLinear regression
Computer implemented methods for generating a non-transient record of feature locations and / or facial expression parameters characterizing a person's face. A video sequence of a specified individual person is received and a feature locator update model is applied to the video sequence. The feature locator update model is derived by defining a set of training images, generating a set of facial feature displacements for each training image with associated image sample vectors, and training a regularized linear regression which maps from image sample vectors to displacement vectors, wherein the regularization includes a spatial smoothness term within the shape-free sample space. A feature location and / or a facial expression parameter is then extracted, based on the feature update model, characterizing the location, and / or the expression, of the feature of the face of the specified individual person.
Owner:IMAGE METRICS LTD
Behavior identification method based on 3D convolution neural network
InactiveCN104281853APrevent overfittingReduce complexityBiological neural network modelsCharacter and pattern recognitionTraining phaseVideo processing
The invention discloses a behavior identification method based on a 3D convolution neural network, and relates to the fields of machine learning, feature matching, mode identification and video image processing. The behavior identification method is divided into two phases including the off-line training phase and the on-line identification phase. In the off-line training phase, sample videos of various behaviors are input, different outputs are obtained through calculation, each output corresponds to one type of behaviors, parameters in the calculation process are modified according to the error between an output vector and a label vector so that all output data errors can be reduced, and labels are added to the outputs according to behavior names of the sample videos corresponding to the outputs after the errors meet requirements. In the on-line identification phase, videos needing behavior identification are input, calculation is conducted on the videos through the same method as the training phase to obtain outputs, the outputs and a sample vector for adding the labels are matched, and the name of the sample label most matched with the sample vector is viewed as a behavior name of the corresponding input video. The behavior identification method has the advantages of being low in complexity, small in calculation amount, high in real-time performance and high in accuracy.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Reduced rank adaptive filter
InactiveUS6956897B1Fast trackingFast convergenceMultiple-port networksAdaptive networkAdaptive filterDigital filter
A reduced rank adaptive digital filtering method is described for a received signal consisting of a sequence of N×1 received vectors. Each received vector is formed from a group of N successive samples. D+1 basis vectors are generated where D is less than N and the dimension of a desired reduced rank subspace. Each successive basis vector is generated by multiplying an immediate preceding basis vector by the covariance matrix for the sequence of received sample vectors and the first basis vector is formed from a given or estimated steering vector. D filter coefficients are generated from correlations between pairs of basis vectors. The adaptive digital filter of the present invention achieves near optimal rank performance with substantially fewer training symbols than heretofore possible.
Owner:NORTHWESTERN UNIV
Hand-writing Chinese character computer generation and beautification method
InactiveCN101393645AAesthetic evaluation possibleImprove the stroke decomposition effectDrawing from basic elementsComputing modelsHandwritingImaging processing
The invention discloses a method for generating and beautifying handwritten characters with a computer. The method is realized by learning a certain amount of hand written character samples. The method comprises the following steps: decomposing and parameterizing the strokes of five to twenty different handwritten character samples for the same character, and converting each character into the form of sample vector by the image processing method; linear interpolation is conducted among characters to obtain new handwritten characters; evaluating each new character by an automatic computer evaluation method of character writing form aesthetic degree; and adjusting interpolation coefficients repeatedly through a nonlinear programming optimization method so as to achieve the effect of beautifying the character. The system of the invention can automatically generate handwritten characters with better aesthetic degree, and improve the aesthetic degree of handwritten characters of a user on the basis of reserving the basic characteristic of the handwriting of the user.
Owner:ZHEJIANG UNIV
N-Gram participle model-based reverse neural network junk mail filter device
InactiveCN101930561AFully characterizedEffective judgmentBiological neural network modelsOffice automationTest sampleSpamming
The invention relates to the technical field of text processing, in particular to an N-Gram participle model-based reverse neural network junk mail filter device. Customized word characteristic items are added to mail particles by using N-Gram technology, and judgment and filter of junk mails are implemented by combining a reverse neural network. The device is implemented by the following steps of: firstly, processing the mails by using a Markov chain and an N-Gram technique, extracting mail sample characteristics, and obtaining a sample mail word-document space by weight calculation and characteristic selection; secondly, matching a mail sample by using the customized word characteristic items to generate a customized characteristic-document space, and combining the document characteristics generated by the two methods to generate a new mail vector space; thirdly, constructing a reverse neural network model, generating characteristic vectors corresponding to network neurons according to the characteristic items of a mail training sample space, and training the network model by using the mail training sample vector space to obtain a trained mail classifier; and finally, generating a test sample vector space by the mail test sample according to the generated characteristic vectors corresponding to the network neurons, and testing the mail type judgment accuracy of the trained mail classifier. The embodiment of the invention can judge the junk mails so as to filter the junk mails.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Transformer partial-discharging mode recognition method based on singular value decomposition algorithm
ActiveCN103077402AImprove efficiencyIncrease profitTesting dielectric strengthTransformers testingSingular value decompositionTransformer
Owner:STATE GRID CORP OF CHINA +1
Data compression for a waveform data analyzer
InactiveUS20080103710A1Effective calculationNoise figure or signal-to-noise ratio measurementAmplifier modifications to reduce noise influenceData compressionTraining period
A compressor for waveforms having at least two waveform states separates the waveform samples into waveform state sample vectors for each waveform state. Waveform state encoders encode the waveform state sample vectors separately to provide compressed waveform data. The waveform state encoder selects waveform state pattern vector and associated codes to represent the waveform state sample vectors. The differences between samples of the waveform state sample vector and waveform state pattern vector are calculated and encoded. Encoding can be lossless or lossy. The waveform state pattern vectors and other parameters for compression are determined during a training period. The waveform state encoders detect features in the waveform state sample vectors and waveform state pattern vectors that are useful for common oscilloscope measurements. Typical waveform states include level states and edge states.
Owner:ALTERA CORP
Multi-user detection
InactiveUS20040248515A1Avoid noiseMinimize replacementEcho effect reductionTransmission control/equalisingMulti user detectionComputer science
A method of finding a maximum likelihood solution for, comprising: providing a sample vector; iteratively match-filtering said sample vector with a coefficient matrix to find a gradient; using the gradient to search for a maximum likelihood solution; and deciding if a found solution of vector data is good enough.
Owner:LENSLET
Detection of Wideband Interference
InactiveUS20100014616A1Distance minimizationNoise varianceError preventionLine-faulsts/interference reductionHide markov modelWideband
A method of detecting interference in a received sample vector using hidden Markov modelling by first estimating noise variance, where estimating noise variance comprises the steps of receiving a sample vector of noise and interference, sorting the sample vector in the frequency domain by order of increasing magnitude to produce an ordered vector, finding a sub-vector of the ordered vector that minimises the distance from a noise measure, and estimating the noise variance.
Owner:CALLAGHAN INNOVATION
Automatic temperature override pattern recognition system
ActiveUS20150158368A1Air-treating devicesDigital data processing detailsCommunications systemNetwork packet
Each vehicle in a fleet comprises a climate controller having an auto mode. The auto mode controls climate actuators in response to a model relating sensed climate conditions to respective settings for the actuators. The vehicle has a buffer memory periodically storing sample vectors comprised of actuator / operation settings and sensed climate conditions. A user interface in the vehicle is responsive to a user override commands to modify respective operation settings while in auto mode. Each vehicle has a wireless communication system for sending data packages to a remote server when the user generates the override. Each data package is comprised of a plurality of stored sample vectors and an identification of the override command A central database associated with the remote server receives the data packages from the fleet vehicles in order to identify patterns within the received vectors that are associated with any given override command
Owner:FORD GLOBAL TECH LLC
Method for recognizing transformer partial discharge pattern based on singular value decomposition algorithm
InactiveUS20150185270A1Simple processImprove algorithm efficiencyTesting dielectric strengthTransformers testingTransformerDimensionality reduction
A method for recognizing a transformer partial discharge pattern based on a singular value decomposition (SVD) algorithm includes a training model and a classification recognizing process, comprising: firstly setting up an experimental environment having artificial defects, collecting at least one datum sample, and calculating statistical feature parameters of each datum sample to form a datum sample matrix; performing singular value decomposition on the datum sample matrix and determining an order of an optimal retention matrix by judging whether a feature of a retention matrix is clear, so as to obtain a type feature description matrix and a class-center description vector group after dimensionality reduction; preprocessing samples to be recognized to obtain a sample vector, and performing linear transformation on the sample vector utilizing a type space description matrix.
Owner:STATE GRID CORP OF CHINA
Fmcw-type radar level gauge
ActiveUS20120299767A1High bandwidthIncrease the bandwidth without increasing the sweep timeLevel indicatorsAntenna detailsMicrowaveRadar
A level gauge using microwaves to determine a distance to a surface of a product in a tank, wherein a measurement signal comprises a first frequency sweep, and a second frequency sweep, and a mixer is arranged to mix the measurement signal with an echo signal to form a first IF signal based on the first frequency sweep, and a second IF signal based on the second frequency sweep. Processing circuitry is adapted to sample the first IF signal and the second IF signal, to form a combined sample vector including samples from each tank signal, and to determine the distance based on the combined sample vector.By combining the samples from two (or more) different sweeps, the number of samples and the bandwidth can both be increased, thus maintaining the range L. However, as the samples are obtained from two separate sweeps, the sweep time for each individual sweep does not need to be increased, and the average power consumption can be maintained.
Owner:ROSEMOUNT TANK RADAR
Overlapped-between-clusters-oriented method for classifying two types of texts
InactiveCN101876987AImprove performanceSpecial data processing applicationsTest sampleText categorization
The invention discloses an overlapped-between-clusters-oriented method for classifying two types of texts. The method comprises the following steps of: forming training sample vectors, identifying training samples in an overlapped area and judging whether the training samples are in the overlapped area between clusters; re-dividing training sample vector sets, constructing a first layer classifier on the newly divided training sample vector sets; in various kinds of training sample sets in the overlapped area between clusters, extracting binary word strings formed by the words, of which adjacent words are verbs or nouns, as characteristics to construct a second layer classifier; and finally, performing the first layer classification on test samples, if the conditions are met, identifying the test samples by the second layer classifier, and merging the results of the two layers of classifiers to obtain a final classification result. The method is applied in the fields of classification of the texts with a higher overlapped-between-clusters degree, information filtration and information monitoring, and can ensure the accurate classification of the texts with a higher overlapped-between-clusters degree.
Owner:THE PLA INFORMATION ENG UNIV
RFID positioning method based on adaptive deep belief network
ActiveCN107247260AAccurate and efficient processingAlleviate the problem of slow learning rateUsing reradiationDeep belief networkEstimation methods
The invention relates to an RFID positioning method based on an adaptive deep belief network. The method comprises a step of laying the positions of a reader and reference tags, and calculating distances from the reference tags to the reader, a step of allowing the reader to send electromagnetic wave signals to the reference tags and receive signal intensity RSSI values, and constructing a training sample vector matrix, a step of constructing the adaptive deep belief network, taking the RSSI value of each reference tag as an input value, and taking the distance d of each reference tag as an output value, a step of using a contrastive divergence algorithm to complete the pretraining of a network parameter, a step of using an adaptive moment estimation method to adjust a weight of each layer of a deep learning network, and a step of allowing the reader to send a signal to a tag to be measured and receive an RSSI value, and using the deep belief network to predict the position of the tag to be measured. According to the method, the adaptive deep belief network is used, a nonlinear relationship between a signal intensity value and the distance is constructed, a cross entropy cost function is used, and a problem of a slow learning rate is alleviated.
Owner:合肥庐阳科技创新集团有限公司
Topic-considered machine reading understanding model generation method and system
ActiveCN110096698AImprove reading comprehensionSemantic analysisNeural architecturesMethod of undetermined coefficientsHigh weight
The invention discloses a topic-considered machine reading understanding model generation method and system. According to the present invention, the potential topic information in the training sampledata is extracted, and the topic information is utilized to supervise the training of a reading understanding model, so that the effect of the reading understanding model is improved. According to themodel disclosed by the invention, a plurality of topics corresponding to the training samples are extracted before model training, and the topic information of the samples is utilized to improve theeffect of the machine reading understanding work. The basic process of the method comprises the following steps of processing each training sample, and finding out a vector representation capable of representing the sample; clustering the samples, and solving a mean value of the similar sample vectors as the vector representation of the topic; during matching and outputting, using an attention mechanism for representing the higher weight of the words with higher similarity with the topic vector of the sample for the vector. In addition, the training data can obtain a better effect after beingsubjected to better data cleaning, and better topic vector representation can be obtained after noise is reduced.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)
Method and arrangement for asynchronous rsrp measurement in an LTE ue receiver
InactiveUS20120099632A1Shorten the construction periodReduce processingModulated-carrier systemsTransmission monitoringEngineeringFrequency shift
In 3GPP LTE, user equipment must be able to report reference signal received power (RSRP) measurement to the serving cell's base station. A low-complexity method for asynchronous RSRP measurement in an LTE user equipment receiver is provided which comprises frequency shifting the received signal so that the upper or lower half band becomes centered around the DC frequency; decimating the received signal to a width of n·2m samples, n being the reference symbol spacing in the received signal; dividing the samples into n sample vectors with a length of 2m each, superimposing said n sample vectors; and performing FFT operation on the superimposed signal.
Owner:INTEL CORP
Analog circuit fault diagnosis method based on depth learning and complex characteristics
The invention discloses an analog circuit fault diagnosis method based on depth learning and complex characteristics. A fault-free state and all fault states are simulated by using simulation software; different representative working frequency points are set successively; an amplitude and phase of a fault-free signal are measured at each measuring point and a real value and an imaginary value of the signal are obtained by calculation; the real values and the imaginary values are processed to form sample vectors; and tag marking is carried out according to a fault state. A classification network is constructed by using a self-coding network and a classifier; training is carried out by using the sample vectors and the corresponding tags; when a fault diagnosis needs to be carried out on the analog circuit, different representative working frequency points are set successively; current amplitudes and phase are measured at all measuring points; sample vectors are constructed according to a pattern; the sample vectors are inputted into the trained classification network to obtain a classification result, thereby obtaining a fault diagnosis result. According to the analog circuit provided by the invention, on the basis of combination of the self-coding network with complex characteristics of signals, the accuracy of analog circuit fault diagnosis is improved.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Fuzzy classification technology-based slope reliability parameter obtaining method and apparatus
ActiveCN107229768AImprove accuracyDesign optimisation/simulationMachine learningSlope stability analysisTest sample
Embodiments of the invention provide a fuzzy classification technology-based slope reliability parameter obtaining method and apparatus, and belong to the field of data processing. The method comprises the steps of generating k training sample vectors through an orthogonal design method according to mean values and standard deviations corresponding to m uncertainty parameters respectively; according to the k training sample vectors and one or more deterministic parameter values, obtaining slope stability coefficients corresponding to the k training sample vectors through a slope stability analysis method; by taking the k training sample vectors as independent variables and taking the slope stability coefficients corresponding to the k training sample vectors as dependent variables, forming a mapping relationship, and obtaining a mapping relationship expression through a support vector machine algorithm; and according to randomly generated N to-be-tested sample vectors obeying joint probability distribution, the mapping relationship expression and a preset instability state fuzzy judgment function, obtaining slope reliability parameters. The slope stability is quantized through the instability state fuzzy judgment function, so that the accuracy of the slope reliability parameters is improved.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)
Clock processing logic and method for determining clock signal characteristics in reference voltage and temperature varying environments
InactiveUS7061294B1Simple and cost-effective implementationDigital storageElectric pulse generatorEdge filterVoltage reference
Clock processing logic and method for determining clock signal characteristics in reference voltage and temperature varying environments are described. A sample vector is characterized by bit locations corresponding to sequentially increasing delay values so that values stored in such bit locations indicate clock signal edges where value transitions occur. In one embodiment, edge detection logic and sensitivity adjustment logic are used in determining the clock period from such a sample vector. In another embodiment, an edge filter, sample accumulation logic, and clock period and jitter processing logic are used in determining an average clock period and clock jitter from a predefined number of such sample vectors.
Owner:SK HYNIX INC
Systems and methods for detection of a target sound
A system for detection of a target sound in an environment of a vehicle, includes an audio sensor, a computer processor, and a memory storing digital target sound templates produced by converting samples of the target sound in accordance with conversion parameters. The computer processor receives the sample sound signal from the audio sensor, converts the sample sound signal to a digital sample vector in accordance with the conversion parameters, compares the vector to each of the templates to determine if a degree of similarity of the vector to any one of the templates exceeds a predetermined threshold value, and notifies a user or a vehicle control system if the threshold value is exceeded.
Owner:SOLTARE INC
Method and device for detecting junk mail
ActiveCN104967558ASolve linearly inseparable problemsGuaranteed detection accuracyData switching networksSupport vector machineLexicon
The invention provides a method and device for detecting a junk mail. The method includes: generating a sample vector according to a sample library and a feature word lexicon which includes normal mail type feature words and junk mail type feature words which are extracted from sample mails of the sample library; selecting a linear kernel function of a support vector machine, using the sample vector as input and training to obtain a classification function; determining weights of feature words in the feature word lexicon according to a coefficient of the classification function, picking up feature words whose weights are nonzero values to generate a feature word set, and determining a judging threshold value according to an offset of the classification function; and making statistics of a sum of the weights of the feature words contained in a mail to be detected according to the feature word set, and judging the mail to be a junk mail when the sum of the weights exceeds the judging threshold value. The method for detecting a junk mail saves the calculation amount of a detection process, and improves detection efficiency under the condition of guaranteeing detection precision.
Owner:NEUSOFT CORP
Generative confrontation network-based method for writing calligraphy by robot
ActiveCN108764054ASolve the difficulty of manual inputImprove learning abilityCharacter and pattern recognitionNeural architecturesGenerative adversarial networkNetwork model
The invention discloses a generative confrontation network-based method for writing calligraphy by a robot and relates to the robot. The method comprises the steps of collecting standard calligraphy stroke data, collating and sorting according to stroke types and making annotations; training two deep neural networks: a generative network G and a confrontation network D, on the basis of a generative confrontation network model; inputting a randomly sampled vector into the generative network G to obtain the probability distribution of track points of strokes; obtaining position information of the strokes from the probability distribution by adopting a sampling method and writing the strokes to a drawing board by a calligraphic robot and shooting and recording images of the strokes by a camera after the writing; and preprocessing the to-be-processed images and inputting into the confrontation network D to train and adjusting parameters to achieve convergence. The generation mechanism hasa good learning ability to enable the calligraphic robot to have a generation mechanism that can automatically generate various styles of strokes, so that the difficulty that a large number of labor power is consumed to manually input, of a current calligraphic robot, is solved.
Owner:XIAMEN UNIV
Method for improving velocity spectrum resolution by using phase information
ActiveCN102073064AHigh-resolutionAvoid Velocity Analysis EffectsSeismic signal processingNormal moveoutVelocity spectrum
The invention relates to a technique for processing petroleum geophysical prospecting seismic data, which is a method for improving the velocity spectrum resolution by using phase information. The method comprises the following steps of: stimulating and recording seismic waves to obtain a common midpoint gather; performing a first-order derivative operation along a time direction, and performing Hilbert transform to obtain a complex seismic trace; superimposing P(t) traces to obtain the optimal velocity of normal moveout correction (NMO); calculating a velocity spectrum by using a conventional velocity analysis method; and performing side lobe suppression on the selected common midpoint (CMP) for velocity analysis and each time sample vector in SPS to finally obtain the velocity spectrum. By the method, influences on the velocity analysis due to amplitude changes can be avoided, the distribution of noises is converted into the distribution with gauss distribution characteristics, so that influences on the velocity analysis due to abnormal noises can be effectively inhibited, and the resolution of the velocity spectrum and the accuracy of the velocity analysis are improved.
Owner:BC P INC CHINA NAT PETROLEUM CORP +1
Product risk early warning method and device, computer device and storage medium
PendingCN109360105AThe risk analysis results are accurate and effectiveEarly warning information is accurate and effectiveFinanceNeural architecturesNetwork modelData science
The present application relates to the field of artificial intelligence and can be applied to the financial industry, and provides a product risk early warning method and device, a computer device anda storage medium. The methods includes: obtaining product information to be analyzed, carrying out data portrait processing on the product information to be analyzed, obtaining vector data corresponding to product information to be analyzed, the vector data is combined with a plurality of sample vector data of the preset twin neural network model respectively, and the obtained pairs of combined data are input into the preset twin neural network model, the risk probability of the product to be analyzed is obtained, and the risk warning information of the product to be analyzed is pushed according to the risk probability. As that data portrait proces is carried out, The data of the products to be analyzed can be deeply mined, the vector data of the products to be analyzed and the sample vector data can be combined as the input data, and the preset twin neural network model is used to evaluate the similarity of the two input data, so that the risk analysis results and the corresponding warning information can be more accurate and effective.
Owner:PING AN TECH (SHENZHEN) CO LTD
FMCW-type radar level gauge
ActiveUS8497799B2Increase the bandwidth without increasing the sweep timeHigh bandwidthLevel indicatorsAntenna detailsMicrowaveRadar
Owner:ROSEMOUNT TANK RADAR
Millimeter-wave radar environment map construction method and device based on clustering algorithm
ActiveCN112526513AImprove accuracyCharacter and pattern recognitionRadio wave reradiation/reflectionDbscan clusteringMeasurement precision
The invention discloses a millimeter-wave radar environment map construction method and device based on a clustering algorithm. The method comprises the steps that: multi-frame mobile acquisition dataand corresponding pose information of a millimeter-wave radar are acquired; according to the pose information, the coordinate information of the target of the multi-frame mobile acquisition data relative to the radar in a Cartesian coordinate system is processed to obtain combined point cloud data, and the combined point cloud data comprises a plurality of sample vectors; a DBSCAN clustering algorithm is used for carrying out miscellaneous point screening processing on the combined point cloud data, and input parameters of the DBSCAN clustering algorithm are determined according to dimensioninformation of the combined point cloud data and Mahalanobis distance data between sample vectors in the combined point cloud data; a millimeter-wave radar measurement precision model is established by utilizing the combined point cloud data subjected to miscellaneous point screening processing; and a millimeter-wave radar environment map is constructed according to the millimeter-wave radar measurement precision model. The method can effectively improve the accuracy of the millimeter-wave radar environment map.
Owner:BEIJING GENERAL MUNICIPAL ENG DESIGN & RES INST +1
Flexible gaussian minimum shift keying in a cellular internet of things system
ActiveUS20160105891A1Modulated-carrier systemsCriteria allocationFourier transform on finite groupsFrequency-division multiple access
Methods, systems, and devices are described for wireless communication at a UE. A user equipment (UE) may utilize orthogonal frequency division multiple access (OFDMA) for demodulating downlink messages and a combination of Gaussian minimum shift keying (GMSK) and single carrier frequency division multiple access (SC-FDMA) for uplink modulation. The uplink modulation process may include generating a symbol vector with an M-point discrete Fourier transform (DFT), filtering the symbol vector with a frequency domain Gaussian filter, generating a sample vector from the filtered symbol vector utilizing an inverse DFT, and modulating the sample vector utilizing GMSK. In some cases, the uplink modulation may be based on a narrowband resource allocation received from a base station.
Owner:QUALCOMM INC
Efficient near neighbor search (ENN-search) method for high dimensional data sets with noise
InactiveUS6947869B2Quality improvementReduce probabilityAmplifier modifications to reduce noise influenceDigital computer detailsData compressionHigh dimensionality
A nearer neighbor matching and compression method and apparatus provide matching of data vectors to exemplar vectors. A data vector is compared to exemplar vectors contained within a subset of exemplar vectors, i.e., a set of possible exemplar vectors, to find a match. After a match is found, a probability function assigns a probability value based on the probability that a better matching exemplar vector exists. If the probability that a better match exists is greater than a predetermined probability value, the data vector is compared to an additional exemplar vector. If a match is not found, the data vector is added to the set of exemplar vectors. Data compression may be achieved in a hyperspectral image data vector set by replacing each observed data vector representing a respective spatial pixel by reference to a member of the exemplar set that “matches' the data vector. As such, each spatial pixel will be assigned to one of the exemplar vectors.
Owner:THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY OF THE NAVY
Target detection method based on structural type Haar and Adaboost
InactiveCN106971193ATotal number decreasedIncrease training speedCharacter and pattern recognitionVideo monitoringCascading classifiers
The invention discloses a target detection method based on structural type Haar and Adaboost. The method includes following steps: creating a sample, and obtaining a positive example sample vector description file and a counter example sample description file; then creating a structural type Haar characteristic, and performing training according to the structural type Haar characteristic to obtain a weak classifier and a strong classifier; and obtaining a cascaded classifier, and finally performing target detection by employing the obtained cascaded classifier to obtain a final detection result. According to the target detection result obtained by the method, good detection precision can be guaranteed, the false detection rate is reduced, the training time is effectively reduced, and the method can be applied to the fields of intelligent traffic detection, video monitoring, and image identification and search etc.
Owner:NANJING UNIV OF SCI & TECH
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