410results about How to "Accurate expression" patented technology

A computer system enables a user to conveniently fill-out, configure, and submit a structure of interrelated data fields, where the order and type of linking between the fields is user selected. A graphical user interface presents a field template having one or more data fields. The user may extend the electronic form by selecting an expand form field; in response to selection of the expand field, the user interface adds a second field template and a connective field to the display. This second template, like the first, includes one or more data fields. Using a connective field, the user identifies a logical relationship between the first field template and the second field template. For instance, the user may select from Boolean or other connective terms to construct a form having a complex format of interrelated fields. As each new field template is added with its corresponding connective field, the user interface also presents a nesting icon, allowing the user to establish a logical hierarchy between the various field templates.

An obstacle detecting unit detects whether an obstacle exists in an area surrounding a vehicle in the direction a camera installed on the vehicle is pointed. If the obstacle is determined to have a portion at a predetermined height above a road surface with which the vehicle may make initial contact when the vehicle moves toward the obstacle, a virtual projection surface is set to the height of the predicted contact portion and viewpoint conversion processing is performed so as to project pixels of an image captured by the camera onto the virtual projection plane. In this way, the height of the projection plane and the height of the predicted contact portion match each other and the distance between the predicted contact portion and the vehicle is accurately expressed on a bird's-eye view image resulting from the viewpoint conversion.

One or more embodiments of the disclosure include an electronic communication system that allows a user to select, configure, and send an electronic communication element to another user. For example, an electronic communication element can include a symbol, icon, animation, sound, and/or other elements that can be sent via an electronic communication. In particular, one or more embodiments of the electronic communication system allow a user to configure the electronic communication element to send a customized message to another user with the configured communication element.

The present invention is directed to vectors and to methods of using same.

The invention discloses an automatic annotation method and system for an innovative and creative label on the basis of big data. The method comprises the following steps that: using a Sogou corpus to train Word2vector and LDA (Latent Dirichlet Allocation) to obtain a training result set; carrying out word segmentation on the document data of a user browsing page, removing a stop word, and carrying out word filtering processing; for preprocessed document data, combining an improved TextRank algorithm with the Word2vector to calculate a label from the text data; in addition, carrying out calculation on the preprocessed document through the LDA to obtain the label related to a document data theme; and through a label cloud generation way, realizing visualization, and annotating all text label words in the document data so as to bring convenience for users to read and find key content parts.

The invention discloses a searching method and searching equipment. The searching method comprises the following steps: receiving a search keyword input by a user, acquiring at least one search document relating to the search keyword based on the search keyword, and determining the semantic vector of the search keyword; according to the semantic vector of the search keyword and the semantic vector of each search document, calculating the semantic correlation between each search document and the search keyword; according to the semantic correlation, sequencing the search documents and outputting the search documents to the user according to the sequencing result. The semantic vector of the document of a search engine is acquired according to the semantic vector of a document tile, the semantic vector of a document identifier and the semantic vector of a document category, so that the semantic information of the document can be expressed accurately, the precision of the semantic correlation between the document acquired by calculation and the search keyword is improved, the search precision of the search engine is improved, and the user experience on the search engine is improved.

The invention discloses a method for expressing three-dimensional scenes. The method comprises the following steps: firstly, according to input multipath video image sequences and information extracted from each video image sequence, identifying and extracting the semanteme and the edge of an object in an actual scene and acquiring the depth information of the three-dimensional scene, and segmenting a video image at a middle view point on the basis of the depth information; adding block information extracted from video images of other view points in the blocked position of a blocked object according to the block relation between the segmented objects; and finally, according to the extracted depth information, expressing the depth of each object by a depth function or by both depth level and depth change mode. The invention also discloses a television system for processing input multipath video image data by the method.

Waveform data representative of singing voices of a singing music piece are analyzed to generate melody component data representative of variation over time in fundamental frequency component presumed to represent a melody in the singing voices. Then, through machine learning that uses score data representative of a musical score of the singing music piece and the melody component data, a melody component model, representative of a variation component presumed to represent the melody among the variation over time in fundamental frequency component, is generated for each combination of notes. Parameters defining the melody component models and note identifiers indicative of the combinations of notes whose variation over time in fundamental frequency component are represented by the melody component models are stored into a pitch curve generating database in association with each other.

The invention relates to a method for predicting city traffic accidents based on time-space distribution characteristics. The method comprises: first, in combination of the case information and the space information, creating a case space database and performing pretreatment to the data; then, based on surface area statistics, analyzing the traffic accidents' time-space distribution characteristics; using the global and local self-correlation method to realize the analyzing of the aggregate state; based on the case happening point data, analyzing the traffic accidents' time-space distribution characteristics; through the hierarchical clustering analysis, expressing the distribution rule of the cases hierarchically; through the nuclear density estimation method, expressing the continuous changes and accurate gathering center of the traffic accidents' happening distribution; and finally, utilizing the BP neural network prediction algorithm, using the time-space distribution characteristics of the already happened cases to predict the time-space distribution areas of traffic accidents in the future. According to the invention, in combination with the time-space distribution and through the utilization of big date excavation BP neural network prediction algorithm and the time-space distribution characteristics of the already happened cases to predict the time-space distribution areas of traffic accidents in the future, it is possible to increase the precision, the timeliness and reduce the manual cost.

The invention provides a hadoop-based k-means clustering analysis system and method of a network security log. The hadoop-based k-means clustering analysis system comprises a log data acquisition subsystem, a log data mixing mechanism storage management subsystem and a log data analysis subsystem. The method includes the steps that in a data storage layer, a mixing storage mechanism with Hadoop cooperating with a traditional data warehouse is adopted to store log data, a Hive operation interface is provided in a data access layer, the data storage layer and a computing layer receive instructions from a Hive engine, and efficient query analysis on the data is achieved by being matched with MapReduce through HDFS; when mining analysis is conducted on log data, MapReduce is adopted to conduct clustering mining analysis on the network security log through a k-means algorithm; the framework with the Hadoop cooperating with the traditional data warehouse is adopted, the detects of the traditional data warehouse on the aspects of mass data processing, storage and the like, and meanwhile an original traditional data warehouse is fully used; clustering analysis is conducted through the MapReduce-based k-means algorithm, and safety grade evaluation and early warning can be conducted on log data timely.

The invention provides a method for planning a path of a lift object for a crane. The method comprises the following steps of: projecting an obstacle on a working plane of the crane; performing polar radius-oriented processing on the projection and transforming a coordinate expression form of the obstacle into a polar coordinate expression form; analyzing the obstacle which is positioned on the path of the lift object to ensure that the lift object can pass through the path; and determining a lifting path according to a lifting principle. By the method for planning the path of the lift object for the crane, distances among obstacles can be calculated quickly and efficiently, the planned lifting path can be searched precisely, and the lifting safety and reliability of the lift object can be improved.

The invention relates to a method for re-identifying persons on the basis of deep learning encoding models. The method includes steps of firstly, encoding initial SIFT features in bottom-up modes by the aid of unsupervised RBM (restricted Boltzmann machine) networks to obtain visual dictionaries; secondly, carrying out supervised fine adjustment on integral network parameters in top-down modes; thirdly, carrying out supervised fine adjustment on the initial visual dictionaries by the aid of error back propagation and acquiring new image expression modes, namely, image deep learning representation vectors, of video images; fourthly, training linear SVM (support vector machine) classifiers by the aid of the image deep learning representation vectors so as to classify and identify pedestrians. The method has the advantages that the problems of poor effects and low robustness due to poor surveillance video quality and viewing angle and illumination difference of the traditional technologies for extracting features and the problem of high computational complexity of the traditional classifiers can be effectively solved by the aid of the method; the person target detection accuracy and the feature expression performance can be effectively improved, and the pedestrians in surveillance video can be efficiently identified.

An image generating method for producing a pictorial image at higher speed when a three-dimensional object is arranged in an object space. The image generating method has: operating a normal line to a surface of a three-dimensional object; setting a plurality of sampling points within a rendering region on which the three-dimensional object is projected on the basis of a predetermined viewpoint; and rendering the three-dimensional object by performing processing for determining an arrangement angle of a predetermined brush image on the basis of the normal line at a position on the surface of the three-dimensional object, corresponding to each of the plurality of sampling points, and arranging the predetermined brush image at the arrangement angle at the position corresponding to each of the plurality of sampling points in the rendering buffer.

The invention discloses a method for identifying multi-view human face based on nonlinear tensor resolution and view manifold, which comprises the following steps: normalizing the size of the multi-view human face; dividing multi-view human face images into a test set and a training set by adopting a method of leaving one out; arraying the human face images in the training set into a form of tensor along the direction of identity, view and pixel information change, resolving tensor data by using high-order singular values to obtain a coefficient matrix of identity, view and pixel factors of the human face images; using a data-concept driving mode to array and interpolate view coefficients to obtain the view manifold of human face; according to the rotating objective sequence of the human face, generating the view manifold through a concept driving mode; using the nonlinear tensor resolution to map the view manifold to a data space of the multi-view human face, obtaining a modular matrix of identity coefficient, and establishing a model of the multi-view human face; and adopting an iterative algorithm based on EM-like to solve a model parameter, and achieving identification by the parameter meeting the minimum reconstructed error criterion. The method has the advantages of high accuracy and high speed, and can be used for complex human face retrieval and identification under different view angles in the field of biological characteristic identification.

The invention discloses a personalized search method for Web service recommendation. The personalized search method comprises the following steps of: 1, preprocessing a WSDL (Web Services Description Language) file, i.e., forming a bag of words through two preprocessing steps of removing stop words and extracting stems; 2, extracting user interest, i.e., calculating weight of each word in the bag of words by using an improved TF-IDF (Term Frequency-Inverse Document Frequency) formula, and multiplying by a time decay factor of the word to obtain a new weight; selecting previous k words according to the weight from large to small as interest words of a user and corresponding weight of each word to form a k-dimension user interest vector; 3, calculating interest similarity, i.e., setting a similarity threshold and selecting the users with interest similarity exceeding the threshold as neighbor users of a target user; and 4, ordering service search results, calculating a recommended predicted value of the service according to similarity of neighbor users and the frequency of selecting service of the users, and arranging the searched results in a descending order according to the recommended predicted value, thereby obtaining the personalized search result.

The invention discloses a text similarity calculation method and device, and relates to the technical field of text processing, which can accurately calculate the similarity between texts in a text with complex expression. The method comprises the steps of obtaining training word segmentation corpora obtained after word segmentation is conducted on text corpora with different sentence lengths; inputting the training word segmentation corpora as training data into a supervision model for training, and constructing a sentence vector conversion model which is used for converting sentences in the text corpus into sentence vectors for representing text characteristics; adjusting characteristic parameters in the sentence vector conversion model according to the sentence vector which is obtained by training and represents the text characteristics; based on the adjusted sentence vector conversion model, performing sentence vector conversion on the plurality of target texts to obtain a plurality of sentence vectors representing the characteristics of the target texts; and calculating the similarity among the plurality of target texts according to the plurality of sentence vectors representing the characteristics of the target texts.

The embodiment of the invention discloses a method, device and equipment of expression recognition. Human face expressions are expressed more accurately according to probability distribution of a plurality of expressions. The expression recognition method comprises the steps that human face area images are extracted from obtained images which is to be recognized and includes human faces; low levelfeatures and high level features are extracted from the human face area images through deep convolutional neural network models, wherein the low level features comprise outlines of facial lines of the human face area images and intensity of each pixel point gray level, the high level features comprise forms of facial features of the human face area images; and the extracted features are combinedthrough the deep convolutional neural network models, the combined features are judged through decision rules obtained from training learning in the deep convolutional neural network models to obtainprobability of M kinds of expression, and the M is a positive integer greater than 1.

A distortion compensating circuit is provided in which, in the polar modulation system, while suppressing increase of compensation data and increase of the circuit scale, a modulated signal can be correctly expressed, or low-distortion characteristics of a power amplifier can be realized.

Based on a steady characteristic compensating circuit 11 which stores an output signal amplitude and output phase characteristics with respect to a control voltage in a steady state, amplitude adjustment is executed on amplitude information r11(t) on which amplitude correction is performed, by a first amplitude information adjusting portion 13, whereby the output-response characteristics of an output signal amplitude of an amplifier with respect to a change of the control voltage can be improved.

The design of new ribozymes capable of self-catalyzed trans-splicing which are based upon the catalytic core of a Group I intron are described. Using this design, it is possible to construct ribozymes capable of efficiently splicing a new 3' exon sequence into any chosen target RNA sequence in a highly precise manner. Inactive pro-ribozyme forms are also described.