Patents
Literature
Patsnap Copilot is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Patsnap Copilot

76 results about "Class diagram" patented technology

In software engineering, a class diagram in the Unified Modeling Language (UML) is a type of static structure diagram that describes the structure of a system by showing the system's classes, their attributes, operations (or methods), and the relationships among objects.

High-resolution SAR image classification method based on non-down-sampling contourlet full-convolution network

ActiveCN107239751AHas the ability to classify and discriminateAvoid duplicationScene recognitionData setClassification methods
A high-resolution SAR image classification method based on a non-down-sampling contourlet full-convolution network is provided, which comprises: inputting a high-resolution SAR image to be classified; performing multi-layer non-down-sampling contourlet transform on each pixel in the image; obtaining the low-frequency coefficient and the high-frequency coefficient of each pixel; selecting and fusing the low-frequency coefficients and high-frequency coefficients to form a pixel-based characteristic matrix F; normalizing the element values in the characteristic matrix F to obtain a normalized characteristic matrix F1; dicing the normalized characteristic matrix F1 to obtain a characteristic block matrix F2 used as sample data; constructing a training data set characteristic matrix W1 and a testing data set characteristic matrix W2; constructing a classification model based on a full convolution neural network; training the classification model; utilizing the well-trained model to classify the testing data set T to obtain the category of each pixel in the testing data set T; comparing the obtained category of each pixel with a class diagram; and calculating the classification accuracy. With the method, the classification accuracy and speed are increased.
Owner:XIDIAN UNIV

Stereoscopic image objective quality evaluation method based on physiological and psychological stereoscopic vision

The invention belongs to the field of image process, and provides a quality evaluation method capable of comprehensively considering physiological and psychological stereoscopic vision clues, and can effectively realize objective quality evaluation on a stereoscopic image. According to the technical scheme of the invention, a stereoscopic image objective quality evaluation method based on physiological and psychological stereoscopic vision comprises the following steps of: a first step of calculating absolute difference of a left view and a right view; a second step of converting the absolute difference into a grey-scale image which is taken as a characteristic parameter capable of representing the quality of a stereoscopic image; a third step of carrying out K-means cluster segmentation on a converted grey-scale image; a fourth step of differentially treating by distributing different weights for different class diagrams; a fifth step of calculating a WMSSIM value between a class diagram of the original stereoscopic image and a class diagram of a distortion stereoscopic image; and a sixth step of finally obtaining stereoscopic image quality evaluation index 3DM. The method is mainly applied to stereoscopic image objective quality evaluation.
Owner:TIANJIN UNIV

Software defect measuring method based on complex network

The invention provides a software defect measuring method based on a complex network. The software defect measuring method based on the complex network can predict defects existing in a software system, so that influences in the future are prevented. The software defect measuring method based on the complex network comprises the following steps that first, a system class diagram is generated reversely according to a system executable file; second, the obtained system class diagram is converted into a network diagram of a software structure, wherein classes represent nodes, and relations between the classes represent edges; third, analysis at the level of the complex network is conducted according to the obtained network diagram, and the average shortest distance, an access degree and a clustering coefficient in complex network parameters are calculated by means of complex parameters, and a complex characteristic measuring value of software is obtained; fourth, a hierarchy measuring system is imported according to an object-oriented level, and an object-oriented characteristic measuring value of the software is obtained; fifth, the complex characteristic measuring value obtained in the third step and the object-oriented characteristic measuring value obtained in the fourth step are contrasted with known standard values, an assessment is conducted, and a defect measuring result prediction about the analyzed software is obtained finally.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY

Fault tree generation method for extended UML class diagram model of safety-critical system

The embodiment of the invention provides a fault tree generation method for an extended UML class diagram model of a safety-critical system. The method comprises the steps of constructing the UML class diagram model of the safety-critical system, wherein all classes in the UML class diagram model comprise attributes and operations and have a certain relation, and the element semantics of the model is extended by a stereotype; storing the UML class diagram model into a file with a set format, analyzing the file with the set format corresponding to the UML class diagram model by a set information extraction algorithm to extract all the classes and the attributes and the operation information which correspond to all the classes in the UML class diagram model, and generating a fault tree of the UML class diagram model according to a set fault tree generation algorithm. According to the method disclosed by the embodiment of the invention, relevant safety analysis information is successfully embedded into the designed model of the safety-critical system, so that automatic conversion between the designed model of the system and a safety model of the system is realized, and the design fault of the safety-critical system can be effectively overcome.
Owner:BEIJING JIAOTONG UNIV

Method for extracting and retrieving textural features from ground digital nephograms

The invention discloses a method for extracting and retrieving textural features from ground digital nephograms, which comprises an extracting method and a retrieving method. The extracting method comprises the following steps: converting a RGB three-channel ground digital nephogram into single-channel pixel class diagrams; analyzing the pixel class diagrams and establishing co-occurrence matrixes to obtain histogram vectors of the co-occurrence matrixes; merging the histogram vectors of the pixel class co-occurrence matrixes to establish textural feature vectors of the ground digital nephogram; and storing the textural feature vectors into the nephogram database. The retrieving method comprises the following steps: extracting the textural features of the sample nephogram according to the feature extracting method; orderly calculating the similarity between the textural features of the sample nephogram and the textural features of every nephogram in the nephogram database; and displaying the most similar nephograms as retrieval results. The invention can automatically analyze and extract the effective textural features of the ground digital nephogram, and automatically retrieve the result nephograms similar to the sample nephogram from the nephogram database.
Owner:CHINESE ACAD OF METEOROLOGICAL SCI +1
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products