406results about How to "Improve match rate" patented technology

Steps after a user finds an attractive product until he or she buys it are successively performed so that he or she can buy it stressfreely. The user photographs an attractive product with a portable camera telephone terminal 1 and transmits image data 7 to a server 3 through Internet 2. The server 3 has a DB 4 in which images such as various types of products, persons, and logo marks are registered and a DB 5 in which related information of image data registered in the DB 4 is registered. The server 3 performs an image recognizing process for the image data 7, retrieves data that match the image data 7 with a high match rate from the image data registered in the DB 4, and extracts corresponding related information from the DB 5. The related information is provided to the user through the Internet 2. By only transmitting the image data 7, the user can obtain related information of an attractive product. When the user accesses a site 6 for the product corresponding to the related information, he or she can obtain detailed information and buy the product.

Ink strokes of cursive writing are segmented to make the cursive writing more like print writing, particularly with respect to the number of strokes of a character. A stroke-segmentation module first finds the local extrema points on a stroke of input ink. Then the local extrema points are stepped through, two (or three) at a time. The stroke-segmentation module may compare the three (or four) ink segments that are adjacent to the two (or three) local extrema points to a set of predefined stroke-segmentation patterns to find a closest matching pattern. Strokes are then segmented based on a stroke-segmentation rule that corresponds to the closest matching pattern. Additional stroke segmentation may be performed based on the change of curvature of the segmented ink strokes. Then, a character-recognition module performs character recognition processing by comparing the segmented ink strokes to prototype samples at least some of which have been similarly segmented.

The invention discloses a method for quickly matching Chinese addresses in a multi-level manner on the basis of address feature words, and belongs to the field of data spatial research in the geographic information science. The method particularly includes two links of creating standard Chinese address matching dictionaries and matching the addresses. Chinese words of standard Chinese addresses are segmented on the word segmentation basis of the address feature words, the standard Chinese address matching dictionaries are created by the aid of double-array trie trees and Hash operation, database retrieval modes are replaced by bidirectional scanning and Hash operation, and geographic spatial coordinates of the Chinese addresses to be matched are acquired, so that the Chinese addresses can be matched. The method has the advantages that integral address matching procedures can be completed in memories of computers, and the address matching speed can be increased owing to bidirectional scanning and a simultaneous word segmentation and matching mode; the problem that partial Chinese addresses cannot be matched due to missing of address elements can be solved according to Chinese address classifying, layering and combining rules, and the address matching accuracy can be improved.

The invention discloses a POS-aided method for matching aerial images, which comprises the following steps: firstly, utilizing an exterior orientation element obtained by the POS to construct a homonymous nucleofilament constraint equation and predict the initial parallax of an image; then, establishing an image pyramid according to the initial parallax and an approximate one-dimensional image correlation which carries out nucleofilament constraint layer by layer on the image of the pyramid; and finally adopting the matching of least-square images to confirm homonymous image points and pick mismatched points, thereby obtaining the homonymous image points of the images to be matched. The invention which adopts the POS-aided image matching method to automatically measure image points has the advantages that not only the application potential of the POS can be fully developed; but also the matching rate and the matching efficiency of automatically rotating points can be improved; and the problems that the rotating points of the images are so difficult to be matched that the rotating points are required to be measured manually and interactively are solved, for example, the rotational angles of certain images are too large, the image texture is not obvious, and the topographic relief is bigger.

There is provided a method of processing a digital image including: (a) obtaining a plurality of images; (b) converting the plurality of images into histograms; (c) setting one of the plurality of images as a reference image and another of the plurality of images as a comparison target image; (d) adjusting a distribution of the histogram of the reference image to match a distribution of the histogram of the comparison target image to produce an adjusted reference image; (e) comparing a difference between the adjusted reference image and the comparison target image to produce a masking image; (f) applying the masking image to the comparison target image to produce an adjusted comparison target image; and (g) combining the reference image and the adjusted comparison target image to produce a high dynamic range (HDR) image. Accordingly, even if there is a complex motion on a subject, a clear image without an image overlap or a ghost effect may be obtained when producing the HDR image.

The invention discloses a method for re-identifying vehicles in sequence images of a mentoring video. The method comprises the following steps of performing image feature extraction: for all shot video data, firstly detecting out vehicle images appearing under a camera, dividing the vehicle images of the monitoring video into a plurality of equilong vehicle image sequences according to the vehicles and the camera, calculating grayscale histograms of two channels Cr and Cb in a YCrCb space, and finally obtaining vehicle contour images by using a Gabor filter and original image convolution; performing a set-to-set-based metric learning method: training a step of learning a metric function of relative distances between vehicle target image sequences, namely, performing metric learning based on a thought of maximization of a probability that inner-class distances are shorter than between-class distances; and performing between-set metric learning-based vehicle re-identification. According to the method, the complexity of an algorithm is lowered while feature dimensions are reduced; and after between-set distance measure is added based on a re-identification effect, the identification rate of the algorithm is increased and the identification effect is improved.

The invention relates to the field of image processing and image identification, and particularly relates to a human motion local characteristic representation method and an application in behavior identification thereof. The human motion local characteristic representation method comprises the following steps that firstly kinetic energy of human bone joints, the position coordinates of the human bone joints, the direction change vectors of the human bone joints and posture potential energy of the human bone joints are extracted from the perspective of energy according to human behavior biological and kinematic characteristics so that a local characteristic combination matrix is constructed; and then dimension reduction is performed on the local characteristic matrix by utilizing K-means clustering and bag of word (BOW) characteristics are extracted, characteristic vectors used for behavior identification are formed through combination of human joint angle characteristics, and the characteristic vectors are applied to the field of human behavior identification so that the method has great effect through experimental verification.

The embodiment of the invention provides a leader sequence transmission method, device and system, and relates to the field of communications. According to the leader sequence transmission method, device and system, the intensity of leader sequence signals received by a base station can be enhanced, therefore, the matching probability of the base station is increased, and the efficiency at which a user has access to the base station is increased. The method includes the steps that system information broadcasted by the base station or a physical broadcast channel (PBCH) is obtained, wherein the system information or the PBCH comprises a preset physical random access channel (PRACH), the preset PRACH comprises preset m wireless frames, and m is a positive integer; it is determined that the repetition times of leader sequences used for random access at preset resource positions of the preset PRACH are n, wherein n is larger than or equal to 1 and smaller than or equal to 10 m; the leader sequences are sent at the n preset resource positions of the RRACH to the base station.

The invention discloses a method and a device for pushing news information in a browser. The method comprises the steps of receiving a request of loading a webpage submitted by a user; when the webpage corresponding to the request is loaded, acquiring the news information corresponding to the webpage, wherein the news information comprises thematic information; generating a first display window on the loaded webpage; and displaying the thematic information in the first display window. According to the method, the news information related to other platforms is sought to push according to the labels of the web pages, so that the unicity and one-sidedness of single platform news information can be prevented; furthermore, the intelligence of other persons and the collective can be utilized to remedy the limitations of definition and manual work, so that the manual operation cost can be greatly reduced.

The embodiment of the present invention discloses a picture recommending method, apparatus and system. According to the embodiment of the present invention, tags with same, close or related semanteme are clustered to obtain clustered tags; then when picture recommendation needs to be carried out, picture information of a current picture is acquired; according to the picture information, a corresponding clustered tag set is acquired and according to the clustered tag set, a picture is selected to generate a candidate pool; and then a similarity between the current picture and each picture in the candidate pool is calculated and on the basis of the similarity, picture recommendation is carried out. According to the scheme, a matching ratio can be greatly improved, a statistical effect is strengthened, and a picture recommending effect is improved integrally.

A social media identity/construct is created for a person by locating social media profiles of the person at least by one or both of i) recognizing image(s) in one or more social media postings related to the person and ii) correlating geolocation data embedded in one or more social media postings related to the person or the person's social media connections, analyzing, monitor social media outlets and channels to create a social media profile for the person.

The invention discloses an auxiliary design method of virtual terminals on the basis of a general template and key character matching. The auxiliary design method comprises the following steps of: firstly manually associating the virtual terminals as the general template, then conforming the position of the virtual terminals in a file to be associated with the positions of the virtual terminals with the same function in the general template by key character matching, so that the automatic association of most virtual terminals with different types in different manufacturers is realized; and for fewer virtual terminals without automatic association, the manual association can be carried out after the search range is shrunk. The auxiliary design method disclosed by the invention has the advantages that design workload can be effectively reduced and the design efficiency and the design quality are improved.

The present application relates to the field of computer technology, in particular to a pharmaceutical data processing method, apparatus, computer device and storage medium based on machine learning.The method comprises the following steps of: acquiring a plurality of drug data, wherein the drug data comprises an instruction manual, the instruction manual comprises a plurality of fields and corresponding text contents; extracting the text content corresponding to the preset fields in the instruction manual; obtaining a classifier, inputting the text content into the classifier, outputting a disease class corresponding to the drug data through the classifier, and adding the disease class to the drug data; obtaining a disease classification coding table, wherein the disease classification coding table comprises a disease category and corresponding coding data; the disease category of the drug data is matched with the disease classification coding table, and the corresponding coding datais added to the drug data. The method can effectively improve the matching rate of the drug data and the corresponding disease categories.

The invention relates to a battery grouping method. The method comprises the following steps: (1) discharging batteries to be grouped according to a preset multiple ratio so as to obtain a discharge curve of voltage changing; (2) selecting the voltage platform of each battery to be grouped, and calculating the average value of the voltage platform; (3) calculating the differences or quotients between each voltage platform value and the average value, and taking the calculated differences or quotients as the comparative values; (4) sequencing the comparative values from large to small or otherwise, individually carrying out subtraction calculation or division calculation on two neighbored comparative values, taking the calculation results as the deviation values, and when the absolute value of a deviation value is larger than a first preset differential voltage factor or less than a second present differential voltage factor, dividing the two batteries corresponding to the two neighbored comparative values into different groups.

The invention relates to a geocoding-free rapid image splicing method of a low-altitude unmanned plane. A key frame image is extracted from a video to carry out geocoding-free rapid image splicing to generate a panoramic image. The method comprises the following steps: extracting a key frame image from a video stream to obtain all to-be-spliced images; carrying out feature point extraction including establishing a multi-dimensional space unit, constructing a pyramid image, determining a key point position, and removing an unstable point on all to-be-spliced images and carrying out screening on the key point by using a SUSAN algorithm to obtain a final feature point; carrying out feature matching according to respective feature points of a corresponding reference image and a to-be-matched image; and carrying out smoothening on the to-be-spliced images by using a gain compensation method, carrying out weighted average fusion on spliced overlapped areas to eliminate seams and sawteeth, and carrying out splicing to generate a panoramic image. According to the technical scheme, the method can be applied to fields of emergency surveying and mapping, disaster prevention and mitigation, land monitoring, emergency monitoring, pipeline layout and inspection of the oil sector, and circuit layout and power line inspection of the power sector and the like.

The present application relates to a text perception based emotion feedback method and apparatus, a computer device and a storage medium. The method comprises: calculating obtained to-be-fed back textcontent by using a text content perceptor to obtain the first weight distribution ratio and the second weight distribution ratio; inputting the to-be-fed back text content into a trained neural network to obtain an emotion classification result; calculating emotion words in the to-be-fed back text content according to a preset rule in a preset dictionary to obtain a corresponding emotion index result; according to the first weight distribution ratio and the second weight distribution ratio, weighting the emotion classification result and the emotion index result to obtain an emotion analysisresult; obtaining an emotional opinion result corresponding to the to-be-fed back text content; and according to the emotion analysis result and the emotional opinion result, selecting a target emotional feedback comment reply corresponding to the to-be-fed back text content from a preset comment reply association library. By virtue of the technical scheme of the present application, the matchingrate between the to-be-fed back text content and the target emotional feedback reply can be improved.

The invention discloses a fabric property picture collection and recognition method based on deep learning. The method comprises the steps that multiple fabric property pictures are acquired, macro information and micro information of the fabric property pictures are collected, and a training set is generated; the training set is trained through a deep learning model; deep features which are trained through the deep learning model and contain global information and local information at the same time are extracted, and linear discriminant analysis is performed on the deep features to complete training of the deep learning model; and fabric recognition is performed through a cosine distance according to the trained deep learning model. Through the method, multiple fabric property recognition problems including weaving process problems, background color process problems, surface process problems, printing process problems, spinning process problems and the like are solved, meanwhile, the trained model contains the local information and the global information at the same time, and the accurate recognition rate and the matching rate of a local pattern and a global pattern of a fabric are increased. The invention furthermore discloses a fabric property picture collection and recognition system based on deep learning.

The invention discloses a real-time image splicing method for police unmanned aerial vehicle investigation and evidence obtaining. The method includes the three steps of improved ORB algorithm operation, image registration and image fusion. According to the method, a multi-scale space is constructed; a significance analysis model is adopted to obtain an optimal angle point detection threshold value, and feature points are extracted; an ORB descriptor is adopted to describe the feature points; and a Hamming distance and RANSAC-combined method is adopted to achieve fast matching. As indicated by results, an improved ORB algorithm maintains the superiority of speed, and the matching rate of the improved ORB algorithm is improved as for images on which scale, angle of view, rotation and illumination change occur.

The invention discloses a deep learning-based small-area fingerprint comparison method. The method comprises the following steps of 1) finding position and direction information of a feature point in a small-area fingerprint; 2) according to the obtained position and direction information of the detail feature point in the step 1), performing rotation normalization on an image by taking the feature point as a center and the direction of the feature point as an X axis, and capturing a small block B of a set size; 3) performing convolutional network training: adopting a deep residual error network for a network model of a convolutional neural network, and training a training sample by using a Caffe framework; 4) performing semantic feature extraction; 5) performing fingerprint registration: enabling a user to perform registration in combination with a corresponding instruction in a registration process, wherein a registration template is composed of a feature point union set of a registration fingerprint image; and 6) performing fingerprint comparison, wherein a comparison score is determined by a mean value of a plurality of maximum values of similarity in to-be-matched images and the registration template. The deep learning-based small-area fingerprint comparison method provided by the invention is effectively suitable for small-area fingerprint comparison and is high in reliability.

The invention provides a embedded link short message point-to-point identification method and system. The invention comprises: embedding a plug-in unit of handset software into handset, and converting the conventional point-to-point short message into identification short message; or, a end-to-end direct sending of point-to-point identification service technology user. A short message center gateway forwards short messages, a searching server analyzes, matches short messages, adds identification, and returns the text identification of point-to-point short message. The steps is: receiving a SMS information form a friend, analyzing the message, matching the message content according to the message identification keyword object base, implanting corresponding link and identification respectively, writing the message with implanted point-to-point identification into inbox and storing, and displaying to the user. The invention can increase inquiry result accuracy rate, improve matching speed and searching efficiency, and can represent the new technology development tendency.