221results about How to "Reduce the difficulty of identification" patented technology

The invention relates to an emotion recognition method and system and an intelligent nursing system using the method. The emotion recognition method comprises the steps that a tested face image and an electroencephalogram signal at the same moment or in the same time period are acquired; the tested face image and the electroencephalogram signal are processed to obtain an expression parameter value and an inner emotion parameter value respectively; data fusion processing is performed on the expression parameter value and the inner emotion parameter value to obtain an emotion fusion parameter value; and a current emotion of a tested face is recognized in a pre-stored emotion fusion database according to the emotion fusion parameter value to obtain emotion information. In this way, the information fusion technology is utilized to process a face and a body brain wave in a combined mode from face image processing and body brain wave processing, body emotion recognition is realized, the accuracy and reliability of emotion recognition are improved, recognition difficulty is lowered, and influences of individual differences on emotion recognition are avoided.

The invention relates to mobile phone voice control technology and discloses a voice control method of functions of a mobile phone, which is realized by voice recognition technology. The method comprises the following steps that: a user inputs selected voice key words into the mobile phone and setting the mapping relationship between the input voice key words and the functions of the mobile phone to form a voice control instruction collection; and in a voice control mode, the mobile phone automatically executes a function corresponding to a voice command when the voice command captured by the mobile phone is the same as a voice command preset by the user.

The invention provides an identification method for turnout faults. The method comprises steps as follows: a curve of each action of a turnout is collected; the obtained turnout action curves are divided into normal curves and fault curves; for the normal curves and the fault curves, one normal curve and one fault curve with the most representative characteristics are selected as representative curves of the normal curves and the fault curves respectively; similarity 1 of a to-be-identified curve and the representative normal curve and similarity 2 of the to-be-identified curve with the fault representative curve are calculated with a similarity algorithm; the similarity 1 and the similarity 2 obtained through calculation are compared, if the similarity 1 is larger than the similarity 2, the curve is a normal curve, and if the similarity 1 is smaller than the similarity 2, the curve is a fault curve. According to the identification method for the turnout faults, the problems of missing report and mistaken report caused by the fact that the turnout fault type is judged through artificial experience in the prior art are solved, so that the turnout fault category is automatically identified, repair efficiency and system reliability are improved, and traffic safety is guaranteed.

The invention relates to a generative adversarial network-based remote sensing image thin cloud removal method. The method includes the following steps that: step 1, a thin cloud removal system modelis established; step 2, a network model is designed; step 3, an identification criterion function is constructed; step 4, the thin cloud removal system performs identification; and step 5, thin cloudsin a remote sensing image are removed. According to the method of the invention, the generative adversarial network is adopted to construct the model of an image thin cloud removal problem and perform system identification on the model, thereby realizing end-to-end thin cloud removal; and the constructed criterion function combines the errors of data distribution and reconstruction accuracy, so that the system can better learn the characteristics of data, thus, achieving the removal of the thin clouds. The method provided by the invention has a capacity to adaptively remove uneven thin clouds. With the method adopted, a restored image has high color and texture consistency.

The invention discloses a method for analyzing amine substances in dansyl chloride derived-plasma based on liquid chromatography mass spectrometry. The method is characterized in that dansyl chloride is used as a derivatization reagent to perform derivatization on a metabolite containing primary amine and secondary amine, therefore the retention capability of the amine substances in reversion phase chromatography is increased, the ionization efficiency in mass spectrometric detection is increased, and the purpose of increasing the quantitative accuracy and detection sensitivity of the amine substances is achieved. The method has wide coverage for amine metabolites (comprising amino acid, methylation products, acetylation products, dipeptide and the like), can utilize 100 [mu]L of plasma samples to detect 113 amine substances, supplies the outline information of metabolome of the amine substances, and has the characteristics of good specificity, high accuracy and repeatability, less reagent consumption and the like.

The invention relates to an automatic classification system of aerial photographing line patrol images based on depth learning. The method comprises the following steps of: establishing a line patrolimage classification image library and a label library thereof; establishing a deep learning model, including VGGNet, ResNet, DenseNet, NasNet and other high performance classification models; training a classification model, and randomly performing data enhancement operation on the input data of each iteration in the training process, including rotation, filling cut and grayscale; integrating thefour trained models and obtaining the integrated model; setting classification rules, inputting the images to be detected into the integrated model, taking the three image categories with the first three confidence levels as the classification results of the images to be detected, and copying and storing the results to the servers of the three categories for archiving; continuously optimizing theclassification model, and periodically upgrading the performance of the automatic classification system.

The invention relates to a method for identifying a relationship between a transformer area phase sequence and line households. The method comprises the steps of: acquiring an active current value ofa low-voltage outlet line of each phase of the target transformer area, an active current value data and voltage time sequence data of each electric meter, and voltage time sequence data of a three-phase bus at a distribution transformer low-voltage side; classifying types of the electric meters according to the voltage time sequence data, and acquiring electric meter sets; determining the electric meter set to which the low-voltage outlet line of each phase is to be assigned according to the active current value of the low-voltage outlet line of each phase, the active current values and the voltage time sequence data of the electric meters, the voltage time sequence data of the three-phase bus at the distribution transformer low-voltage side and the electric meter set; and combining arbitrary electric meter sets in electric meter sets of each type, and matching the combined electric meter set to be an electric meter classification set Gamma of a phase low-voltage outgoing line i if asum of the active current values after combination and an active current value of the phase low-voltage outgoing line i satisfy a first preset condition. The method and the device have the advantagesof low identification difficulty, high precision, no need of additionally arranging other terminal equipment, high operability and small operation and maintenance pressure.

A capacitive touch keyboard includes an insulating substrate that defines a plurality of press key zones, and a first and a second conductive layers, both disposed on the insulating substrate. Each conductive layer includes a plurality of electrode lines arranged in two different directions. Each electrode line includes a plurality of electrode units connected in series. Each electrode unit is disposed at a position corresponding to a respective one of the press key zones. For each of the press key zones, the electrode units of the first the second conductive layers that are disposed therein are adjacent to each other and cooperate to form a touch sensing structure.

The present invention provides an application icon display method and apparatus. The method comprises: displaying a virtual three-dimensional stereoscopic control on a touch screen of a terminal device, and setting an application icon on an outer surface of the stereoscopic control; and based on an operation performed on the touch screen by a user, triggering the stereoscopic control to rotate to rapidly reach an application icon wanted by the user. The apparatus comprises a display module and a control module. According to the method and apparatus provided by the present invention, application icons are displayed in a stereoscopic manner, so that a user can see as many as possible application icons simultaneously on the touch screen of the terminal device; and by controlling the rotation of the virtual three-dimensional stereoscopic control, the application icon that is wanted by the user and that is on the virtual three-dimensional stereoscopic control can be rapidly reached. The search time is short, and the identification difficulty is low, thereby greatly improving use experience of the user.

The invention discloses a method for estimating the remaining power of an electric vehicle power battery. The method comprises steps that based on the volume Kalman algorithm, a model for estimating the remaining power of the power battery is established; polarization internal resistance Rp(k), polarization capacitance Cp(k), equivalent ohmic internal resistance R0(k), the remaining power SOC (k)and an end voltage Ut(k) of the power battery at the time k are obtained; an open circuit voltage UOC(k) of the power battery at the time k is calculated; a state estimation error delta e(k) and a noise error V(k) are calculated; the BP neural network based on width learning is constructed, the delta e(k) and the V(k) are inputted into the BP neural network, and a variance compensation value deltaQk of process noise distribution at the time k and a variance compensation value delta Rk of observed noise distribution are outputted by the BP neural network; the delta Qk and the delta Rk are utilized to compensate Qk-1 and Rk-1 at the time k-1, and Qk and Rk at the time k are generated; a value of x(k+1) of the model for estimating the remaining power of the power battery is calculated through the volume Kalman algorithm, and the remaining power SOC (k+1) at the final (k+1) time is obtained. The method is advantaged in that the remaining power of the power battery can be rapidly and accurately estimated.

A valuable file identification method includes step 1: selecting a characteristic area of the valuable file, and extracting a valuable file characteristic for last classification; step 2: an input valuable file is fast classified according to the extracted valuable file characteristic in step 1 to gain the banknote kind, denomination, direction and image quality information of the valuable file, and the banknote with better image quality and bad image quality are selected; step 3: an image restoration technique is utilized based on a partial differential equation to restore the old banknote image; step 4: the new banknote is directly identified and the old banknote is identified via the restored image to judge the authenticity of the current banknote; step 5: a result is output. The method enables eliminating restoration treatment for images comprising good quality and uninterested area, and saving time and improving system processing efficiency. A valuable file identification system and a valuable file identification device are also disclosed.

The invention discloses a digital counter-forgery printing method. The method includes batch printing of 'surface information', 'common counter-forgery printing feature', and 'independent counter-forgery printing feature information'; wherein, the 'surface information' and 'common counter-forgery printing feature' will be sent to printing factories, which will carry out the 'preliminary printing' through the traditional counter-forgery printing means, and reserve the region for 'independent counter-forgery printing feature information'; the region will be printed under the control of computer programs for 'secondary printing'. The method can be used for independent counter-forgery marks, which are printed with a plurality of feature information through the computer coding technique to have a stark contract among different marks. In addition, the changing method is direct and can be understood easily, so consumers and users can identify the marks conveniently. The technique can be widely used for the printing of various counter-forgery marks.

The invention provides an antenna controller for an advanced broadcasting system-satellite (ABS-S) satellite signal mobile-satellite, and belongs to the technical field of antenna control of the mobile-satellite. The antenna controller solves the problems that the antenna controller cannot accurately identify an ABS-S standard satellite, is inconvenient for system upgrading, and complex in control and operation and the like in the prior art. The antenna controller is independent of a mobile-satellite antenna, is connected with the mobile-satellite antenna and a satellite receiver respectively, and comprises a main control circuit, a power supply management circuit, and a liquid crystal display (LCD) liquid crystal screen and a key circuit which are connected with the main control circuit respectively, wherein the power supply management circuit is connected with the main control circuit, supplies power to the main control circuit, and can convert input direct current voltage into required voltage; and the main control circuit can distinguish the voltage of the satellite receiver, and simultaneously the main control circuit normally communicates with the mobile satellite antenna and controls the mobile satellite antenna until a target satellite is locked. The antenna controller can accurately identify the ABS-S standard satellite, and is convenient for system upgrading and simple and convenient for control and operation.

The invention provides a turnout action reference curve selection method and an application thereof. The method comprises the steps of obtaining N action curves of a same turnout through a turnout microcomputer monitoring system, obtaining action time of the N curves, selecting the action time with a highest repetition number in the N action time, and marking the action time with the highest repetition number as Tx; assuming that M curves with action time lengths of Tx exist, and renumbering the M curves; for the M curves, dividing each curve into P equally divided parts according to the action time, and for a current value of a jth moment of the ith curve, obtaining current value matrixes I of the M curves in sequence for all the M curves; for M current values of any moment tj, calculating out a clustering center by utilizing a clustering algorithm, and marking a current value of the clustering center as C(j), wherein C(j) is the current value of the clustering center; and calculatingclustering centers of P moments in sequence, and by analyzing the clustering centers, selecting out a curve with a highest clustering frequency as a reference curve. Based on the reference curve, anabnormal curve diagnosis method is obtained by utilizing a similarity method.

The present invention discloses a radar networking identification target method, belonging to the field of the radar technology. The method comprises: s radars are configured to respectively measure n attributes of a detection target, forming s groups of radar measurement data, and belonging the detection target to one of the possible targets, wherein each attribute of each possible target has one specific value range. According to the invention, the anti-interference capability of an identification system is improved, the identification difficulty is reduced, and the identification accuracy is improved; the identification classification process of the method is performed from top to bottom, is more simple and reliable relative to the current technology, and has high popularization and application values.

The invention discloses an internet-of-things terminal intelligent configuration method and system based on appearance information recognition. The method comprises the following steps of: carrying out photographing on controlled equipment by a camera and obtaining appearance information of the controlled equipment; transferring the appearance information of the controlled equipment to a home control center by an internet of things; and carrying out matched processing on the appearance information of the controlled equipment and internal digital codes of the same controlled equipment as complete identification information of a controlled object, and returning a remote controller for operation of the controlled equipment. According to the invention, due to adoption of matching of the appearance information of the controlled equipment and the internal digital codes of the same controlled equipment as the complete identification information of the controlled object, the external characteristics of different household appliances are different completely, so that the recognition difficulty for different household appliances is greatly reduced, the recognition accuracy is improved, further recognition software can be optimized and used hardware equipment also can be simplified.

The invention discloses a vehicle identification method based on fusion of radar and vision information. The vehicle identification method based on fusion of radar and vision information includes thefollowing steps: S100, entering all the information of a vehicle to be identified; S200, acquiring the current positional information and the motion state information of the vehicle; S300, acquiring the appearance information of the vehicle to be identified; S400, comparing the acquired appearance information of the vehicle to be identified with the entered vehicle information; and S500, recordingand uploading the information of the illegal vehicle and the vehicle driver. The vehicle identification method based on fusion of radar and vision information monitors the vehicles on the road in real time through the method of integrating the radar with vision information, determines the best position of shooting through the radar, can capture the clear image of the vehicle to be identified, canobtain the information of the vehicle to be identified through vision information processing, can determine whether the driver has illegal behavior through information comparison, and can greatly improve the accuracy and efficiency of vehicle identification through the method of combining the radar and the vision information.

The invention discloses a method for automatically acquiring a fetal key section ultrasonic video center dynamic period video, which specifically comprises the following steps of: firstly, positioninga heart part which is continuously deformed by using a target tracking technology, and then primarily identifying diastolic and systolic end stages by using a classification method, so as to obtain arough heart period boundary frame; and finally, using a cross gating bilinear matching model for checking and finely positioning a fragment matched with the standard video in the long video, so thata complete cardiac cycle video under a related standard section can be more accurately matched from two aspects of obvious boundary frames in the cardiac cycle video and dynamic matching in the middle. The invention aims to intelligently and automatically intercept a fetal cardiac cycle video from an ultrasonic video by using deep learning, and provide the most direct and effective basis for subsequent intelligent diagnosis.

The invention discloses a semantic similarity-based industry type recommendation method and a device, equipment and a medium, and the method comprises the steps: generating an enterprise operation description text and a plurality of industry type description texts corresponding to a target enterprise based on a target enterprise name when the target enterprise name is received; preprocessing the enterprise operation description text to obtain a first keyword set, and preprocessing the plurality of industry type description texts to obtain a plurality of second keyword sets; calculating semantic similarity between the first keyword set and each second keyword set, and generating a semantic similarity set; wherein the semantic similarity is obtained on the basis of a pre-trained Word2Vec language model; and recommending an industry type corresponding to the target enterprise name based on the semantic similarity set. According to the invention, the identification difficulty of the industry type to which the enterprise belongs can be reduced, and the monitoring efficiency of the supervision department is improved.

The invention discloses an object pose detection method and device. The object pose detection method comprises receiving an original image acquired by a camera, extracting and obtaining a marked code image from the original image, wherein the marked code image is an image of a marked code attached to the object to be detected; obtaining the pose of the marked code through calculation in dependence on the marked code image and a pre-generated pose calculating model, wherein the pose of the marked code includes the rotation amount and the displacement amount of the marked code relative to the reference pose; obtaining the current pose of the object to be detected through calculation in dependence on the pose of the marked code. According to the invention, the object pose detection process can be simplified, the efficiency of the detection process can be improved, and the accuracy of the detection result can be improved.

The invention relates to a method for simplifying an electric power system synthetic load model and identifying model parameters, and belongs to the technical field of electric power system load stability monitoring. According to the method, the internal relationship between parameters of an induction motor is deeply analyzed, and on this basis, by converting the input-output relationship of the model, a simplified electric power system synthetic load model is provided. According to the simplified electric power system synthetic load model, possible steady-state operation states of multiple sets of simplified electric power system synthetic load models are preset, parameter identification is carried out through the least square method on the basis of a state equation of the part of the induction motor of the simplified electric power system synthetic load model, corresponding indexes are provided to reflect identification precision, and the set model with the highest precision is selected from all preset steady state conditions, and an identification result corresponding to the set of model is used as the final identification result. The method has high generalization performance and feasibility, and can accurately and quickly identify the parameters of the electric power system synthetic load model.