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4595results about How to "Improve search efficiency" patented technology

Intelligent safety monitoring system and method based on multilevel filtering face recognition

The invention discloses a method based on multilevel filtering face recognition. The method comprises the following steps of: collecting a face image of a detected man through an image collection system on a user terminal; automatically detecting and partitioning an exact position of a face from the collected face image by a face detection and positioning system, and performing intelligent indication and image quality real-time monitoring on a face image collection process through an automatic and real-time face image quality detection system; extracting characteristic points from the face image of the user terminal according to an image quality detection threshold value, and generating corresponding target face templates; and performing real-time comparison on a face to be recognized which is detected by a client and a known face database based on a multilevel filter searching algorithm through a background server, finding out the face template having the highest matching score, judging according to a preset threshold value of the system and determining identity information of the shot man in real time. The invention also provides an intelligent identity recognition and safety monitoring system based on a multilevel face filtering and searching technology with high reliability and flexibility.
Owner:CHANGZHOU RUICHI ELECTRONICS TECH

Wind power forecasting method based on genetic algorithm optimization BP neural network

The invention discloses a wind power forecasting method based on a genetic algorithm optimization BP neural network, comprising the steps: acquiring forecasting reference data from a data processing module of a wind power forecasting system; establishing a forecasting model of the BP neural network to the reference data, adopting a plurality of population codes corresponding to different structures of the BP neural network, encoding the weight number and threshold of the neural network by every population to generate individuals with different lengths, evolving and optimizing every population by using selection, intersection and variation operations of the genetic algorithm, and finally judging convergence conditions and selecting optimal individual; then initiating the neural network, further training the network by using momentum BP algorithm with variable learning rate till up to convergence, forecasting wind power by using the network; and finally, repeatedly using a forecasted valve to carry out a plurality of times of forecasting in a circle of forecast for realizing multi-step forecasting with spacing time interval. In the invention, the forecasting precision is improved, the calculation time is decreased, and the stability is enhanced.
Owner:SOUTH CHINA UNIV OF TECH +1

Method and device for providing error correcting prompt and input method system

The invention discloses a method for providing an error correcting prompt. The method comprises the following steps of: obtaining a character string of a cursor position on a display screen; analyzing the obtained character string and judging whether the obtained character string needs processing; and supplying the prompt of the character string needing processing to a user. The invention also discloses a device for providing the error correcting prompt and an input method system. The method and the device not only can supply the error correcting prompt to characters, which are being edited by the user by using the input method, but also can supply the prompt of the character string needing processing, which is displayed on the display screen, to the user as well as supply a complementing or error correcting choice to the user so as to help the user rapidly and correctly position the character string needing processing and finish inputting and modifying a text, so an input process becomes more smooth. Since the input method has an error correcting prompt function, the dependence of the user on editing environments such as Word and the like is reduced and the character inputting quality of the user in different situations can be improved.
Owner:BEIJING SOGOU TECHNOLOGY DEVELOPMENT CO LTD

Autonomous quadrotor unmanned aerial vehicle positioning and controlling method based on laser radar

The invention belongs to the technical field of autonomous flight control research on a quadrotor unmanned aerial vehicle, and discloses an autonomous positioning method based on a two-dimensional laser radar as well as a design method for a quadrotor unmanned aerial vehicle control system based on the positioning method and other onboard MEMS (micro electro mechanical systems) chips. According to the technical scheme adopted by the invention, the autonomous quadrotor unmanned aerial vehicle positioning and controlling method based on the laser radar comprises the following steps: preliminarily positioning the unmanned aerial vehicle in the horizontal direction by utilizing the two-dimensional laser radar, and acquiring a preliminary position value of the unmanned aerial vehicle in the height direction by utilizing an onboard barometer; then acquiring the position information of the unmanned aerial vehicle with high frequency by combining with onboard accelerometer chips by utilizing a complementary filtering algorithm; and finally, applying to unmanned aerial vehicle control systems without GPS signals based on the position information. The autonomous quadrotor unmanned aerial vehicle positioning and controlling method based on the laser radar, which is provided by the invention, is mainly applied to design and manufacturing of autonomous flight control devices of the unmanned aerial vehicle.
Owner:TIANJIN UNIV

Sparse dimension reduction-based spectral hash indexing method

The invention discloses a sparse dimension reduction-based spectral hash indexing method, which comprises the following steps: 1) extracting image low-level features of an original image by using an SIFT method; 2) clustering the image low-level features by using a K-means method, and using each cluster center as a sight word; 3) reducing the dimensions of the vectors the sight words by using a sparse component analysis method directly and making the vectors sparse; 4) resolving an Euclidean-to-Hamming space mapping function by using the characteristic equation and characteristic roots of a weighted Laplace-Beltrami operator so as to obtain a low-dimension Hamming space vector; and 5) for an image to be searched, the Hamming distance between the image to be searched and the original image in the low-dimensional Hamming space and using the Hamming distance as the image similarity computation result. In the invention, the sparse dimension reduction mode instead of a spectral has principle component analysis dimension reduction mode is adopted, so the interpretability of the result is improved; and the searching problem of the Euclidean space is mapped into the Hamming space, and the search efficiency is improved.
Owner:ZHEJIANG UNIV

Unmanned vehicle semantic map model building method and application method thereof to unmanned vehicle

The invention discloses an unmanned vehicle semantic map model building method and an application method thereof to an unmanned vehicle. Extraction of a conceptual structure indicates that key map elements such as road networks, road traffic participants and traffic rules related in the running process of the unmanned vehicle are reasonably abstracted into different conceptual types, establishment of the semantic relation between concepts refers to establishment of map concept semantic hierarchical relations and incidence relations, and living examples of the conceptual types and the semantic relation among the living examples are established in an instantiated manner to finally obtain a semantic map for the unmanned vehicle. A map data structure applicable to the unmanned vehicle is built, the sufficient semantic relation among the map elements is designed, the semantic map is generated, semantic reasoning is performed according to the semantic map, a globally planned route, the current position and orientation of the unmanned vehicle and peripheral real-time obstacle information to obtain local scene information of the unmanned vehicle, scene understanding of the unmanned vehicle is realized, and the unmanned vehicle is assisted in behavior decision.
Owner:HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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