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480 results about "Feature coding" patented technology
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Feature Coding Standards and Geodatabase Design The application of a coding standard can be independent of a specific data product or specification, and in fact, any geographic feature in any database can be assigned some major and minor codes based on a coding standard.
Method of image feature coding and method of image search
A feature coding unit extracts and encodes a feature of a video signal so as to generate a feature stream. A feature identifying unit checks a decoded feature obtained as a result of decoding the feature stream against a search key from a user for a match so that a video content requested by the user is retrieved.
Owner:MITSUBISHI ELECTRIC CORP
Infrared behavior identification method based on adaptive fusion of artificial design feature and depth learning feature
ActiveCN105787458AImprove reliabilityInnovative feature fusionCharacter and pattern recognitionNeural learning methodsData setFeature coding
The invention relates to an infrared behavior identification method based on adaptive fusion of an artificial design feature and a depth learning feature. The method comprises: S1, improved dense track feature extraction is carried out on an original video by using an artificial design feature module; S2, feature coding is carried out on the extracted artificial design feature; S3, with a CNN feature module, optic flow information extraction is carried out on an original video image sequence by using a variation optic flow algorithm, thereby obtaining a corresponding optic flow image sequence; S4, CNN feature extraction is carried out on the optic flow sequence obtained at the S3 by using a convolutional neural network; and S5, a data set is divided into a training set and a testing set; and weight learning is carried out on the training set data by using a weight optimization network, weight fusion is carried out on probability outputs of a CNN feature classification network and an artificial design feature classification network by using the learned weight, an optimal weight is obtained based on a comparison identification result, and then the optimal weight is applied to testing set data classification. According to the method, a novel feature fusion way is provided; and reliability of behavior identification in an infrared video is improved. Therefore, the method has the great significance in a follow-up video analysis.
Owner:CHONGQING UNIV OF POSTS & TELECOMM
Attention mechanism relationship comparison network model method based on small sample learning
ActiveCN110020682AImprove classification accuracyImprove stabilityCharacter and pattern recognitionNeural architecturesModel methodSmall sample
The invention discloses an attention mechanism relationship comparison network model method. An attention relationship comparison network model for small sample learning under a small amount of labeled sample data is constructed. Based on a relational network architecture, the model is divided into a feature coding part, a feature combination part and a relational coding part, the feature coding module is used for extracting image feature information, and the feature combination part is used for recombining the extracted query image feature information with the training image feature information of each group to form a new combined feature map. The relation encoding module performs nonlinear metric learning of the network; by introducing an attention mechanism and a spectrum normalizationmethod into an end-to-end deep convolutional neural network model, the model has higher classification accuracy under the condition of small sample learning, the stability of a final training result of the model is improved, and the image classification accuracy of an existing model in small sample learning is improved.
Owner:BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY +1
Human body movement recognition method based on convolutional neural network feature coding
ActiveCN107169415ASmall amount of calculationImprove accuracyCharacter and pattern recognitionHuman bodyFeature coding
The invention provides a human body movement recognition method based on convolutional neural network feature coding and mainly aims to solve the problems of complicated calculation and low accuracy in the prior art. According to the implementation scheme, TV-L1 is utilized to obtain a video light steam graph; convolutional neural network coding, local feature accumulation coding, dimension-reducing whitening processing and VLAD vector processing are sequentially performed in a video space direction and a light stream movement direction, and space direction VLAD vectors and movement direction VLAD vectors are acquired; and information in the video space direction and information in the light steam movement direction are merged to obtain human body movement classification data, and then classification processing is performed. According to the method, convolutional features are subjected to local feature accumulation coding, so that the recognition rate is increased when complicated background data is processed, and the calculated amount is reduced; the features acquired by fusing video VLAD vectors and light stream VLAD vectors has higher robustness to environmental changes, and the method can be used for performing detection and recognition on human body movement in a monitoring video in areas such as a community, a shopping mall and a privacy occasion.
Owner:XIDIAN UNIV
Semantic segmentation method with second-order pooling
InactiveUS20150104102A1Improve performanceImprove accuracyCharacter and pattern recognitionFree formFeature coding
Feature extraction, coding and pooling, are important components on many contemporary object recognition paradigms. This method explores pooling techniques that encode the second-order statistics of local descriptors inside a region. To achieve this effect, it introduces multiplicative second-order analogues of average and max pooling that together with appropriate non-linearities that lead to exceptional performance on free-form region recognition, without any type of feature coding. Instead of coding, it was found that enriching local descriptors with additional image information leads to large performance gains, especially in conjunction with the proposed pooling methodology. Thus, second-order pooling over free-form regions produces results superior to those of the winning systems in the Pascal VOC 2011 semantic segmentation challenge, with models that are 20,000 times faster.
Owner:UNIV DE COIMBRA OF REITORIA DA UNIV DE COIMBRA
Multi-person posture estimation method based on global information integration
ActiveCN110135375AHigh precisionReduce misconnectionsCharacter and pattern recognitionNeural architecturesEstimation methodsAlgorithm
The invention discloses a multi-person posture estimation method based on global information integration. The multi-person posture estimation method comprises the following steps: carrying out pre-processing on an input image; generating a group of human body boundary frames through a human body detector, and inputting the obtained human body boundary frames into a'feature coding + posture decoding 'module to carry out model training; sequentially predicting the positioning of the key points of each person, and generating a plurality of key point heat maps to represent the position confidenceof each key point; and finally, eliminating redundant attitude estimation through an attitude non-maximum suppression module to obtain a final human body attitude.. By combining different normalization strategies with multi-layer information fusion, the accuracy of multi-person posture estimation can be remarkably improved, false connection can be effectively reduced by adopting a hyperedge geometric constraint strategy, and a posture estimation method which is difficult to encounter in scale change, shielding and complex multi-person scenes can be effectively improved.
Owner:NINGBO INST OF MATERIALS TECH & ENG CHINESE ACADEMY OF SCI
Context pyramid fusion network and image segmentation method
ActiveCN110689083AQuick responseImprove performanceRecognition of medical/anatomical patternsRadiologyFeature coding
The invention discloses a context pyramid fusion network and an image segmentation method, and the context pyramid fusion network comprises a feature coding module which comprises a plurality of feature extraction layers which are connected step by step, and is used for obtaining a feature map of an original image; a plurality of global pyramid guiding modules, connected with the different featureextraction layers respectively and used for fusing the feature maps extracted by the feature extraction layers connected with the global pyramid guiding modules with the feature maps extracted by allthe higher feature extraction layers to obtain global context information and guiding and transmitting the global context information to the feature decoding module through jump connection; a scale sensing pyramid fusion module, connected with the highest feature extraction layer of the feature coding module and used for dynamically selecting a correct receptive field according to the feature maps of different scales and fusing multi-scale context information; and a feature decoding module, used for reconstructing a feature map according to the global context information and the multi-scale context information. The method is good in image segmentation performance, and is better in effectiveness and universality.
Owner:SUZHOU UNIV
Spatial data conversion method and system
ActiveCN105279243AHigh popularityStrong editing functionGeographical information databasesSpecial data processing applicationsGraphicsFeature coding
The invention discloses a spatial data conversion method and system. The method comprises: performing land feature coding, and marking CAD data by adopting GIS codes storing topographical elements; re-drawing graphic data by adopting features corresponding to graphs for the marked CAD data to normalize the CAD data; and converting the normalized CAD data into GIS data. A whole set of processing process is provided through an embodiment of the invention and comprises the functions of land feature batch coding, topologic check, specific graphic layer screening or exporting all data for the GIS and the like.
Owner:张新长
CT image segmentation system based on attention convolutional neural network
ActiveCN111325751AImprove segmentation execution efficiencyReduce lossesImage enhancementImage analysisFeature codingImage segmentation
The invention provides a CT image segmentation system based on an attention convolutional neural network, and the system comprises a feature coding module which uses a parallel convolutional neural network to gradually reduce the size of a feature map of an input image, and achieves the simultaneous extraction of image semantic information and spatial information through the multiplexing of a network layer and the interception and fusion of features of all layers; the semantic information extraction attention module which is used for generating attention features by pooling and further refining the semantic information features extracted by the feature coding module; the feature fusion pooling attention module which is used for fusing the refined semantic information features with the semantic information and spatial information features spliced by the feature coding module to form an attention feature map by using parallel connection of maximum pooling and average pooling; and the feature map decoding module which is used for gradually and finely restoring the attention feature map into the size of the input image by using a convolution module and an up-sampling module. Accordingto the invention, by fusing the attention module, efficient and accurate image segmentation is realized.
Owner:CHONGQING UNIV OF TECH
Chinese relationship extraction method
ActiveCN110334354AImprove accuracyImprove robustnessCharacter and pattern recognitionNatural language data processingThree levelRelation classification
The invention provides a Chinese relationship extraction method, which comprises the following steps of S1, data preprocessing: performing pre-training processing of multi-granularity information on atext of input data to extract distributed vectors of three levels of characters, words and word meanings in the text; S2, feature coding: taking a bidirectional long-short-term memory network as a basic framework, obtaining hidden state vectors of the characters and hidden state vectors of the words through the distributed vectors of the three levels of the characters, the words and the word meanings, and then obtaining final hidden state vectors of the character level; and S3, relationship classification: learning the final hidden state vector of the word level, and fusing the hidden state vector of the word level into a sentence-level hidden state vector by adopting an attention mechanism of the word level. The problems of word segmentation ambiguity and polysemy ambiguity are effectively solved, the performance of the model on a relation extraction task is greatly improved, and the accuracy and robustness of Chinese relation extraction are improved.
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
Dynamic web page segmentation method
InactiveCN101127044AImprove efficiencyEfficient use ofSpecial data processing applicationsExtensibilityManual segmentation
The utility model relates to a segmentation method of active web page, and is characterized in that the method first receives the content streams of web page and then builds a DOM tree, then makes the nodes of the DOM tree to feature codings, next compares the corresponding nodes of the DOM trees to build common blocks and customization blocks. The utility model can understand and identify the common parts (common blocks) sharing among multi-pages and the special parts of different variation rules (customization blocks) according to the dynamic characteristic and the structural characteristic of the web pages, and dynamically divide the web pages without human interference. The utility model provides a solution with a good expandability, lowers the labour costs for manual segmentation, and can be widely used in technology field of active web page.
Owner:PEKING UNIV
End-to-end classification method of large-scale news text based on Bi-GRU and word vector
InactiveCN108846017AAvoid the curse of dimensionalityImprove performanceSemantic analysisNeural architecturesComputation complexityClassification methods
The invention provides an end-to-end classification method of a large-scale news text based on Bi-GRU and a word vector. The end-to-end classification method comprises the following steps: S1. word Embedding word-level semantic feature representation is performed; S2. the attention weight Bi-GRU word level sentence feature coding model is constructed; S3. the Bi-GRU sentence level feature coding model based on the attention weight is established; S4. hierarchical Softmax is applied to realize end-to-end classification implementation. According to the method, the dimension of the vector can bereduced and the problem that the features are too sparse can be effectively prevented. The final output vector is optimized and the effectiveness of model feature coding is enhanced. The problem thatthe model is difficult to train because of the high dimension can be avoided and the additional semantic information can also be provided. The feature extraction model and various common classifiers can be flexibly combined so as to facilitate replacement and debugging of the classifiers. The computational complexity is reduced from | K | to log | K | in comparison with that of Softmax.
Owner:NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT +1
Training method for classification model, and device and computer server thereof
ActiveCN108664999AImprove training efficiencyCharacter and pattern recognitionApplicability domainFeature coding
The invention discloses a training method for classification models, and a device and a computer server thereof, so as to solve the technical problems that the prior art is low in calculation efficiency and narrow in application range by a semi-supervised learning technology training classification model. The method comprises steps of: constructing an initial classification model, wherein the initial classification model comprises at least one single-mode classification models comprising same classification tasks, and a mode data training set corresponding to each single-mode classification models comprising label training data and label-free training data; and training the initial classification models to obtain target classification models, based on a method of the feature coding distribution that aligning the label training data and the label-free training data in the mode data training set of each single-mode classification models. According to the training method for classification models, the training efficiency of the classification model can be improved, and the application range is wider.
Owner:BEIJING TUSEN ZHITU TECH CO LTD
Zero-sample sketch image retrieval method and system based on graph convolutional neural network
ActiveCN111291212ADigital data information retrievalCharacter and pattern recognitionFeature codingImage retrieval
The invention belongs to the technical field of multimedia information retrieval, and particularly relates to a zero-sample sketch image retrieval method and system based on a graph convolutional neural network. The zero-sample sketch image retrieval system architecture provided by the invention comprises three important components: a feature coding network, a semantic maintenance network and a semantic reconstruction network. The method comprises the steps ofextracing sketches and image visual features through a feature extraction network; processing the visual information of the sketch and the image and the label semantic information of the sketch and the image at the same time through a graph convolution network; establishing a relationship between unseen categories and seen categories;enhancing the generalization ability of the model through a semantic reconstruction network;and finally, the model taking the sketch of which the category is not seen as an input and performing retrieval to find an image similar to the sketch. According to the invention, the variational auto-encoder is adopted to generate semantic information from visual information, so that the generalization ability of the model is further enhanced.
Owner:FUDAN UNIV
Road area detection method
The invention discloses a road area detection method which comprises the following steps: S1, designing a road enhancement data enhancement method, and generating a road data enhancement function; S2,adopting a road data enhancement function, inputting a training sample, and outputting enhanced road data; S3, designing and training a feature coding network model, and outputting a coding feature map through the feature coding network model by using the enhanced road data; and S4, performing designing and training to generate a road segmentation decoding module and a road type classification decoding module, adopting the road segmentation decoding module and the road type classification decoding module, and inputting the coding feature map to output a road segmentation result and a road type classification result. The road area pixel-level segmentation and multi-type classification results are provided, which can be used for detecting passable areas of intelligent vehicles, and providesa basis for obstacle avoidance and path planning of the intelligent vehicles.
Owner:TSINGHUA UNIV
Human-computer identification method and device based on sliding trajectory, and electronic equipment
ActiveCN107679374ALow resolution accuracyImprove accuracyCharacter and pattern recognitionDigital data authenticationState of artFeature coding
The invention provides a human-computer identification method based on a sliding trajectory, belongs to the technical field of computers and is used for solving the problem of low accuracy when a human-computer identification method simulates a sliding trajectory input by a user in the prior art. The method comprises the following steps that: determining the preset dimension feature coding of a historical sliding trajectory which is qualified, and the reference distribution feature of the feature coding of a historical sliding trajectory on the basis of at least one time window; determining the preset dimension feature coding of a real-time sliding trajectory to be verified, and the distribution feature to be verification of the feature coding of a historical sliding trajectory on the basis of at least one time window; and if the distribution feature to be verification on the basis of a certain time window is not matched with the reference distribution feature, determining that the real-time sliding trajectory to be verified is a machine simulation sliding trajectory. By use of the method disclosed by the embodiment of the invention, accuracy for identifying the machine simulationsliding trajectory can be effectively improved.
Owner:北京钱袋宝支付技术有限公司
Three-dimensional target detection method, system and device based on RGB-D
InactiveCN111723721AAvoid lostHigh precisionCharacter and pattern recognitionNeural architecturesVoxelPoint cloud
The invention belongs to the technical field of target detection, particularly relates to a three-dimensional target detection method, system and device based on RGB-D, and aims to solve the problem that efficiency and 3D target detection accuracy cannot be both considered in the prior art. The method comprises the steps of performing feature extraction on a 2D image set of a to-be-detected target, and reversely mapping the 2D image set to a 3D space; performing voxel division on the 3D point cloud data of the to-be-detected target, and performing feature coding through a 3D convolutional neural network in combination with the mapping voxel of the 2D image; aggregating 2D image texture features and 3D point cloud data geometrical features; obtaining a target feature cluster set through a Hough voting network; and obtaining a target bounding box as a three-dimensional target detection result through the target regression and classification network. According to the method, the 2D imagedata is reversely mapped to the 3D space, the 3D point cloud geometrical characteristics and the 2D image texture characteristics are fused, the 3D target detection accuracy is improved, the pre-selected area is generated through adoption of the Hough voting method, and the 3D target detection efficiency is guaranteed.
Owner:COMMUNICATION UNIVERSITY OF CHINA
User concentration degree identification method and system based on hierarchical convolutional neural network
ActiveCN107194371AThe classification result is accurateEasy to classifyAcquiring/recognising facial featuresNeural learning methodsFeature codingLocal binary pattern operator
The invention relates to a user concentration degree identification method based on a hierarchical convolutional neural network. The method comprises the following steps that: obtaining the front side image of a face; according to the front side image of the face, utilizing two local binary pattern operators of an even pattern to calculate a feature coding graph corresponding to the front side image of the face; and according to the feature coding graph under two even patterns and the front side image of the face, adopting a GoogLeNet improved classifier to carry out classified processing to obtain the emotion of the user, and obtaining the user concentration degree according to the emotion. The invention also provides a user concentration degree identification system based on the hierarchical convolutional neural network. The user concentration degree result obtained by the invention is accurate and can be finely decomposed.
Owner:WUXI YSTEN TECH
SAR image segmentation method based on shape completion area chart and feature coding
ActiveCN104463882AGood sealingImprove homogeneityImage enhancementImage analysisFeature codingEWMA chart
The invention discloses an SAR image segmentation method based on a shape completion area chart and feature coding. The method solves the technical problem of closure extraction of SAR image areas. The method includes the steps that a sketch is obtained by utilizing an SAR image initial sketch model; the area chart is obtained by utilizing the area chart completed through sketch lines and based on shapes; the area chart is mapped into an original SAR image space, and then a clustering area, a homogeneous area and a structural area are obtained; characteristic learning and hierarchical clustering are carried out on the clustering area; characteristic learning and hierarchical clustering are carried out on the homogeneous area; segmentation is carried out on the structural area; results of the clustering area, the homogeneous area and the structural area are combined, line targets are marked, and a final SAR image segmentation result is obtained. According to the method, the homogeneous area with the better closure and homogeneity can be extracted, further clustering of the clustering area and the homogeneous area can be well achieved in the characteristic learning and clustering methods applied to the areas, and the method can be used for SAR image segmentation.
Owner:XIDIAN UNIV
Video-based handwritten character input apparatus and method thereof
InactiveUS20100103092A1Input/output for user-computer interactionCathode-ray tube indicatorsGraphicsImaging processing
A video-based character input apparatus includes an image capturing unit, an image processing unit, a one-dimensional feature coding unit, a character database, a character recognizing unit, a display unit, and a stroke feature database. The image capturing unit captures an image. The image processing unit filters a moving track of a fingertip in the picture by detecting a graphic difference, then detecting a skin color and picking out a moving track most corresponding to a point of the object. The one-dimensional feature coding unit takes a stroke with respect to the moving track and converts the stroke into a coding sequence in a one-dimensional string according to a time sequence. The character recognizing unit proceeds with character comparison between the coding sequence in a one-dimensional string and the character database to find out a character having the most similarity for display one the display unit.
Owner:TATUNG UNIVERSITY +1
Method and device for data processing based on federated learning, equipment and medium
PendingCN111178524AEnsure safetyGuaranteed accuracyDigital data protectionNeural learning methodsFeature codingEngineering
The invention discloses a method and a device for data processing based on federated learning, equipment and a medium. The method comprises the following steps executed by a first terminal: determining user feature data shared by a first terminal and a second terminal; performing feature coding processing on the user feature data to obtain to-be-processed feature data; obtaining a model predictionvalue obtained by processing based on the to-be-processed feature data; obtaining a loss value obtained by processing the training label data and the model prediction value by adopting a predefined loss function; sending the external loss value to the second terminal in an encryption mode if the loss value is the external loss value; and determining a target gradient based on the internal loss value and a current model parameter corresponding to the first to-be-trained model if the loss value is an internal loss value, and performing model optimization on the first to-be-trained model according to the target gradient to obtain a target prediction model. The data processing method based on federated learning can effectively improve the model training efficiency and accuracy.
Owner:CHINA PING AN LIFE INSURANCE CO LTD
Prediction method for protein post-translational modification methylation loci
InactiveCN105893787AImprove throughputImprove accuracyProteomicsGenomicsLife activityProtein methylation
The invention discloses a prediction method for protein post-translational modification methylation loci, and belongs to the field of bioinformatics. Protein methylation modification participates in cell functions and many life activities of cell processes, and recognition of protein methylation modification loci has very important significance in understanding of the life activities of cells. The prediction method combines with sequence information, evolutionary information and physical and chemical properties to conduct feature coding on a protein methylation sequence, an information gain optimization feature method is adopted and combines with a support vector machine to construct a prediction model, and it is shown through independent testing results that the prediction method has a good prediction property on the protein methylation loci; meanwhile, a network prediction platform is developed and used for conducting online prediction on the protein methylation loci.
Owner:NANCHANG UNIV
Single-frame image super resolution reconstruction method based on sparse domain selection
ActiveCN105631807ATraining accuratelyGuaranteed accuracyGeometric image transformationObjective qualityReconstruction method
The invention discloses a single-frame image super resolution reconstruction method based on sparse domain selection, mainly to solve the problem that the reconstruction result is poor caused when the existing reconstruction method carries out joint dictionary training. The method comprises steps: low-resolution and high-resolution image training sets are constructed according to an image set; low-resolution and high-resolution feature training sets are constructed according to the image training sets; sparse representation is carried out on the low-resolution feature training set; according to the high-resolution feature training set and a low-resolution feature coding coefficient, an iterative initial value for a high-resolution dictionary is solved; an optimization objective formula for sparse domain selection is constructed, and the high-resolution dictionary, a high-resolution feature coding coefficient and a mapping matrix are solved iteratively; and according to the inputted test image, the high-resolution dictionary, the high-resolution feature coding coefficient and the mapping matrix, a high-resolution image is reconstructed and outputted. The experimental simulation shows that the reconstruction result has higher subjective and objective quality evaluation, and can applied to medical imaging, high-definition video imaging, remote sensing monitoring, traffic and safety monitoring.
Owner:XIDIAN UNIV
Method of image feature coding and method of image search
InactiveUS20050267879A1Drawback can be obviatedTelevision system detailsPulse modulation television signal transmissionFeature codingMethod of images
A feature coding unit extracts and encodes a feature of a video signal so as to generate a feature stream. A feature identifying unit checks a decoded feature obtained as a result of decoding the feature stream against a search key from a user for a match so that a video content requested by the user is retrieved.
Owner:MITSUBISHI ELECTRIC CORP
Method and apparatus for intelligently generating power line route
ActiveCN106250579AImprove efficiencyImprove accuracyGeometric CADSpecial data processing applicationsPath generationFeature coding
The invention relates to a method for intelligently generating a power line route. The method comprises the steps of establishing rules: setting a feature coding rule, and establishing a basic line selection rule and a special line selection rule; establishing line selection regions, determining a target line selection region, and defining a working range; performing barrier analysis, obtaining geographic information data in the involved region according to the line selection regions, establishing a unit grid, judging whether the unit grid involved by geographic information is a barrier grid or not according to the line selection rule, and if yes, attaching attributes of the line selection rule to cells; and generating a line by a line search algorithm according to a cell set in the line selection regions. Compared with the prior art, the method for intelligently generating the power line route has the advantages that a line trend in an engineering region is comprehensively considered, scheme indexes are scientifically analyzed, and key index comparison and analysis are carried out, so that the route generation efficiency and accuracy can be effectively improved. In addition, the invention provides an apparatus for intelligently generating the power line route.
Owner:GUANGDONG KENUO SURVEYING ENG CO LTD
Three-dimensional point cloud target detection method
The invention discloses a three-dimensional point cloud target detection method. The method comprises the following steps: point cloud information of a three-dimensional scene is obtained through a depth sensor and an image sensor to serve as a training data set of a neural network; the point cloud of the target in the scene due to visual angle shielding and long-distance missing is complemented by utilizing a target point cloud model rendered by a computer; two three-dimensional target detection networks are constructed as a virtual training data set, one three-dimensional target detection network being used for inputting real data and the other three-dimensional target detection network being used for inputting virtual data, and the real three-dimensional scene point cloud data and the virtual three-dimensional scene point cloud data are respectively input into respective point cloud feature coding networks for feature extraction; the association perception process is simulated and applied to the deep neural network, and the incomplete point cloud information coding feature domain in the real scene is migrated to the virtual complete point cloud information coding feature domainthrough the transfer learning technology so that the neural network is enabled to actively associate the incomplete point cloud to the complete point cloud.
Owner:FUDAN UNIV
Palmprint recognizing method and device
ActiveCN102254188AImprove matching accuracyLittle changeCharacter and pattern recognitionFeature codingFeature recognition
The invention discloses a palmprint recognizing method and device, relating to the field of biological feature recognition. The palmprint recognizing method comprises the steps of: sequentially intercepting a plurality of local areas on an area in which a palmprint image is interested and acquiring a contrast context vector of each local area; extracting stable areas from the plurality of local areas according to the contrast context vector of each local area; carrying out feature coding on pixels in the stable areas; and carrying out similarity judgment on palmprint features according to theresult of feature coding. According to the invention, prior to feature matching, the stable areas in the area in which a palmprint image is interested are extracted by using the contrast context vectors and the influence on a recognition result when unstable areas are matched is removed; and compared with the prior art, the palmprint recognizing method and device have the advantages that: the matching accuracy is higher and the influence caused by change of palmprint images is less.
Owner:HANVON CORP
Electric cochlea Chinese fixed electric stimulation amplitude changing pattern in vitro voice processing equipment
InactiveCN101301240AImprove performanceReduce power consumptionEar treatmentSpeech recognitionSyllableFeature coding
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
Video processing method and device, electronic equipment and storage medium
PendingCN112464814AImprove accuracyEasy to understandTelevision system detailsCharacter and pattern recognitionFrame (artificial intelligence)Feature coding
The invention discloses a video processing method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence, in particular to the fields of deep learning, model training, knowledge maps, video processing and the like. According to the specific implementation scheme, the method comprises the following steps: acquiring a plurality of first video frames, and performing fine-grained splitting on the plurality of first video frames to obtain a plurality of second video frames; according to multi-modal information related to the plurality of second video frames, performing feature coding on the plurality of second video frames to obtain feature fusion information used for representing multi-modal information fusion; and performing similarity matching on the plurality of second video frames according to the feature fusion information, and obtaining a target video according to a similarity matching result. By adopting the method and the device,the video splitting accuracy can be improved.
Owner:BEIJING BAIDU NETCOM SCI & TECH CO LTD
A continuous action online learning control method and system for an autonomous vehicle
InactiveCN109948781ASolving Dimensionality Reduction Coding ProblemsRealize online learning controlNeural architecturesNeural learning methodsFeature codingHigh dimensional
The invention discloses a continuous action online learning control method and system for an automatic driving vehicle. The continuous action online learning control method comprises the following steps: encoding a perceptual image It through a deep encoding network to obtain an encoding state feature st; respectively inputting encoding state features st into actuators-actuators, wherein the evaluator models all adopt an evaluator network and an actuator network of a cerebellar model neural network, an action at is output through the actuator network, and an actuator is updated through the evaluator network; parameters of an evaluator model. According to the invention, a synthetic deep neural network feature coding technology and an enhanced learning principle are adopted; the learning control problem of a continuous action space is solved under high-dimensional state input; on-line learning control of a continuous action space under large-scale continuous state input can be realized,the learning period is shortened while the learning effect is ensured, the learning process can be quickly converged to obtain a control strategy with a good performance effect, and the data utilization rate is good.
Owner:NAT UNIV OF DEFENSE TECH
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