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495results about How to "Recognition speed is fast" patented technology

Two-dimension image recognition based on three-dimensional model warehouse and object reconstruction method

The invention discloses a two-dimensional image recognition and object reconstruction method based on a three-dimensional model database. The method includes the following steps: a three-dimensional model of an object used for a two-dimensional projection is constructed, the three-dimensional model database is established and an correspondingly correlative attribute database is built up; the two-dimensional projection matching degrees of a two-dimensional image of the object to be recognized and the three-dimensional model of the relative object are compared; as for the two-dimensional projections being in accordance with the matching degree requirement, the object in the correlative attribute database is recognized as the object in the two-dimensional image; and the three-dimensional model in the three-dimensional model database which is correlative to the object in the attribute database is used for reconstructing the object. Due to the adoption of the comparison of the two-dimensional image of the object with the two-dimensional projection of the relative three-dimensional model, the aim of recognizing the object in the two-dimensional image of the object is realized and the two-dimensional images of the object which are photographed in a plurality of angles and from a plurality of directions are recognized; moreover, the aim of reconstructing the object in the two-dimensional image is achieved by using the correlative three-dimensional model; in addition, a paralleling calculation method is adopted to accelerate the speed of the reorganization and the reconstruction.
Owner:深圳市尧元科技有限公司

Front vehicle information structured output method base on concatenated convolutional neural networks

The present invention puts forward a front vehicle information structured output method base on concatenated convolutional neural networks, for mainly solving the problem that a traditional method cannot quickly detect and identify a vehicle body, a license plate and a vehicle logo in one time in a complex environment. The realization process of the front vehicle information structured output method comprises the steps of: 1, acquiring a sample set and selecting a vehicle body initial sample set from the sample set; 2, training the vehicle body initial sample set through a BING (Binarized Normed Gradients) method; 3, respectively training convolutional neural networks of vehicle body, license plate and vehicle logo; 4, judging the area and color of the vehicle body according to the well trained convolutional neural network of vehicle body; 5, judging the area of the license plate and identifying a license plate number according to the well trained convolutional neural network of license plate; 6, judging the area and class of the vehicle logo according to the well trained convolutional neural network of vehicle logo; and 7, outputting the all obtained information to a frame image. The front vehicle information structured output method of the present invention can accurately detect and identify front vehicle information in a complex environment, and can be used for intelligent monitoring, intelligent traffic, driver auxiliary and traffic information detection.
Owner:XIDIAN UNIV

Online decoupling identification method of multiple parameters of PMSM (permanent magnet synchronous motor)

The invention relates to the technical field of PMSMs, solves a coupling problem during online identification of multiple parameters of a surface-mounted type PMSM, and achieves online decoupling identification of PMSM inductance, stator resistance and rotor flux linkage. Accordingly, the technical scheme adopted by the invention is that an online decoupling identification method of multiple parameters of the PMSM comprises the steps as follows: 1) identifying and coupling analysis of parameters of the PMSM; 2) a decoupling identification strategy, wherein voltage deviation before and after D shaft current injection is used for increasing the order of a motor mathematical equation, so that the decoupling identification of multiple parameters of the surface-mounted type PMSM inductance, the stator resistance and the rotor flux linkage are achieved; 3) neural network identifier design, wherein according to a parameter online identification problem of the PMSM, online identification is performed on motor parameters by adopting a self-adaptive neural network structure and a weight convergence algorithm based on a least mean square algorithm. The method is mainly applied to the design and manufacture of the PMSM.
Owner:TIANJIN UNIV

Method for controlling transport robot to autonomously enter elevator

The invention discloses a method for controlling a transport robot to autonomously enter an elevator. The method for controlling the transport robot to autonomously enter the elevator comprises the following steps of navigating the robot to a doorway of the elevator by utilizing an own navigation device of the robot, before the robot enters the elevator, obtaining the position of an elevator call button by utilizing a robot vehicular vision module with depth information collection, triggering the elevator call button according to the position information of the elevator call button, and calling the elevator; obtaining the state information of an elevator door by utilizing a retreating sensor module, and controlling the robot to enter the elevator. According to the method for controlling the transport robot to autonomously enter the elevator, through combining with signals obtained by a Kinect sensor and the retreating sensor module, the past way that an instruction is sent to an elevator controller by a remote control center is thoroughly changed; the past way is changed into the way that an instruction is sent to the robot by the remote control center, the instruction is sent to a PLC (Programmable Logic Controller) by a robot vehicular controller and the elevator is triggered through an arm of the robot; by combining with the redundant design of a full load judgment condition module in the elevator, the control safety performance of the elevator is promoted.
Owner:CENT SOUTH UNIV

Large-scale forging laser radar on-line tri-dimensional measuring device and method

The invention relates to a device and a method for on-line three-dimensional measuring of a laser radar of heavy forging in the measuring technical field, which comprises a two- dimensional laser radar, a servo-motor, a junction box, a rotary main shaft, a spacing and null point sensor, a bearing block which is provided with a bearing, a band brake apparatus, a back supporting stand of the laser radar, an L-shaped mounting bottom plate, a vertical mounting chassis, a movement-control card, a data collecting card, and a computer which is used for processing data. Firstly, the laser radar is positioned on the horizontal surface of a forging axial cord, then four surfaces of the forging are respectively scanned by the laser radar, the two-dimensional laser scanning radar is scanned in the surface which is vertical to an axial cord of the forging, the servo-motor drives the laser radar to rotate in the horizontal surface, thereby the three-dimensional scan of the forging is realized, finally, shape and parameter of the forging are gained through data process, and deviation of the shape of the forging is gained. The invention greatly increases accuracy and speed of identification, enlarges range of application, satisfies measuring requirement of a forging, and effectively increases measuring accuracy and efficiency of the forging.
Owner:SHANGHAI JIAO TONG UNIV

Intelligent canceration cell identification system and method, cloud platform, server and computer

InactiveCN107609503AReduce the possibility of misdiagnosis of symptomsReduce labor costsMedical automated diagnosisCharacter and pattern recognitionNerve networkImaging data
The invention belongs to the technical field of medical image identification and discloses an intelligent canceration cell identification system and a method thereof, a cloud platform, a server and acomputer, which comprise an image acquisition module, a front-end processing module, an expert cloud platform, a diagnosis and suggestion module and a display module. The image acquisition module is used for acquiring the image information of a to-be-identified cell specimen. The front-end processing module is used for carrying out the compression processing on the acquired image data of the to-be-identified cell specimen. The expert cloud platform is used for building a software platform on a cloud server side to establish an image analysis system, establishing a cell image training databaseby utilizing a deep learning convolutional neural network, identifying the acquired image information to find out determined lesion cells, and outputting the determined lesion cells to the display module. The diagnosis and suggestion module is used for displaying a symptom result, uploading the result to the expert cloud platform and providing the condition identification reference information with a certain maximum probability. The display module is used for displaying the symptom result which is accurately identified. According to the invention, a lot of manual time is saved and the missed diagnosis rate is further reduced. Meanwhile, the labor cost is reduced.
Owner:刘宇红 +1

Effective modeling and identification method of moving object behaviors

The invention provides an effective modeling and identification method of moving object behaviors, which comprises the following steps: step 1, firstly extracting local features and then extracting moving features of the moving object behaviors by using a feature extraction module; step 2, fusing the extracted local features and the moving features by using a feature fusion module via a subspace learning method, and reducing dimensions on feature space by using the feature fusion module; and step 3, by combining a prototype learning algorithm with a measure learning algorithm, identifying themoving object behaviors by using a behavior identification module, and evaluating the identified moving object behaviors by using the behavior identification module. In the effective modeling and identification method, the local features and the moving features are subject to feature fusion treatment, thus reducing the dimensionality of the feature space, and improving robustness of feature expression. The effective modeling and identification method has the advantages of low storage and low computational complexity, and has preferable classification and identification performance. The effective modeling and identification method can be used for intelligently monitoring abnormal behaviors in public security fields, thus an alarm is given once the abnormal behavior is found.
Owner:HISCENE INFORMATION TECH CO LTD

Mechanism modeling method for lithium ion battery

The invention belongs to the technical field of a lithium ion power battery of an electric vehicle, relates to a mechanism modeling method for the lithium ion battery and overcomes the defects that the electrochemical model of the lithium ion battery is complex in structure, parameters are difficult to identify and the experimental model precision is low. The mechanism modeling method comprises the following steps of: (1) building a single-particle model of the lithium ion battery; (2) simplifying a solid-phase diffusion equation in the single-particle model of the lithium ion battery by adopting a three-parameter parabola method; (3) identifying unknown parameters in the single-particle model of the lithium ion battery by adopting a bacteria foraging optimization algorithm; and (4) fitting an anode open-circuit voltage expression of the single-particle model of the lithium ion battery. According to the invention, by adopting the three-parameter parabola method, the structure of the single-particle model of the lithium ion battery is simplified; the unknown parameters in the single-particle model of the lithium ion battery are identified by adopting the bacteria foraging optimization algorithm, the identification speed is high, and the globally optimal solution is obtained; and the mechanism modeling method provides theoretical support for the state estimation, life prediction and characteristic analysis of the lithium ion battery.
Owner:JILIN UNIV
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