37results about How to "Save computing power" patented technology

Embodiments of the present application relate to the technical field of human-computer interaction, and disclose a method and device for determining an interactive gesture and an electronic device. The method comprises the following steps: first, target component detection is performed; then, gesture detection and recognition are performed in a local area (around a boundary box) near the target component. In addition, for N gesture detection boxes (multiple users) in a current video frame, M target gesture detection boxes are selected therefrom to perform hand component positioning and gesture recognition processing, which can reduce detection time consumption and improve real-time performance. On this basis, the interactive gesture is determined according to the gesture detection result of the current video frame and the gesture detection results of a plurality of historical video frames, that is, gesture recognition is selectively performed on the user in each frame in a plurality of continuous video frames to determine the interactive gesture, which can reduce the computing power, reduce the time consumption, improve the real-time performance, and improve the accuracy and stability of the interactive gesture. That is, in the multi-user human-computer interaction scene, the interactive gesture can be accurately and timely determined.

The application discloses a routing association relationship updating method, a routing communication method and related devices. The method determines the shortest path of each node in the autonomous network when updating the path, and determines the problem node according to the comparison result between the shortest path of each node and the historical path. Finally, according to the routing prefix in the problem node association prefix set, the target next hop block associated with the routing prefix is selected from the pre-stored next hop block. Then, the next hop block associated with the first prefix is updated according to the target next hop block and the shortest path of the problem node. The next hop block of the application is an index representing the forwarding address of the message. The update of the next hop block associated with the routing prefix is the update of the forwarding address of the message. The flow does not need to re-decide the next hop address of each routing prefix based on the shortest path of all nodes when updating the path, which saves the computing power and improves the network performance.

The application provides a multi-inverter hybrid system transient stability boundary delineation method based on reverse integration, and belongs to the field of electrical engineering. The delineation method combines a circuit model of a grid-constructed inverter, a grid-following inverter and an infinite grid hybrid system and a virtual synchronous machine mathematical model of the grid-constructed inverter, derives a second-order differential-algebraic equation set of the hybrid system, further obtains system steady-state equilibrium points by solving the equation set and classifies, and reversely integrates from the type I unstable equilibrium point to obtain a transient stability boundary of the hybrid system. The application is simple and intuitive, has a solid theoretical basis, can quickly and accurately identify the transient stability boundary of the grid-connected inverter system, and has important significance for analyzing the transient stability of the multi-grid-connected inverter hybrid system.

This invention provides a face action recognition method, comprising: acquiring the face key point recognition results of a local face parsing service for a sequence of images to be recognized, wherein the sequence of images to be recognized is obtained by a face image acquisition service based on face action recognition instructions; determining the organ key point sequence corresponding to each target facial organ based on the face key point recognition results, wherein the target facial organs are determined according to the face action recognition instructions; determining the action recognition results corresponding to each target facial organ based on the organ key point sequence; and determining the face action recognition results of the front-end browser based on the action recognition results. Face action recognition can be directly performed in the front-end browser based on the organ key point sequence, reducing server-side computing power. Furthermore, using the organ key point sequence for face action recognition eliminates the need to directly capture temporal dependencies in the sequence of images to be recognized, reducing the parameter requirements of the local face parsing service, thereby reducing development and deployment costs.

The invention discloses a large-range collaborative navigation method for an extraterrestrial patroller, and relates to the field of computer vision, visual navigation and map splicing. The method comprises the following steps: performing significance analysis based on spectral residual for a right monocular camera, focusing on sight capture of a typical feature region, establishing a visual odometer model of inertial IMU pre-integration, and performing back-end optimization driven by a factor graph; establishing a plurality of extraterrestrial patroller similar region search models based on an improved bag-of-words model, introducing a similarity relative scoring function based on a norm form, setting a relative threshold value of a similarity suppression function, and obtaining an image overlapping region; according to the method, the calculation capability of an airborne computer is considered, a sparse feature point map and patroller pose splicing model is established, complete splicing of overlapped area maps is completed through splicing of small sparse feature point maps, and the splicing precision and the splicing efficiency are improved.

The application discloses a wavelength modulation-direct absorption dual-mode wide-range gas concentration detection method with temperature self-adaptive threshold, and belongs to the technical field of tunable diode laser absorption spectrum gas detection. The existing pure mode switching scheme generally uses a fixed concentration threshold, and temperature change will cause the switching point to deviate from the optimal error balance point, aiming at the problem, the application calibrates the critical peak absorbance as a unified reference under the reference temperature, and also calculates the line intensity under different temperatures to generate a corresponding lookup table; during work, the current line intensity is obtained by real-time temperature lookup table, and the concentration switching threshold is dynamically updated, the wavelength modulation mode is used in the initial detection stage, when the concentration continuously exceeds the threshold, the direct absorption mode is switched to, and when the concentration is lower than the hysteresis threshold, it is switched back, the application uses dynamic threshold updating to make the switching point correspond to the optimal error balance point of the two methods at all times, and the sensitivity at low concentration and the linearity at high concentration are considered.

This application provides a license plate recognition method, apparatus, electronic device, and storage medium. The method includes: sliding a sliding window of preset length and width along the long side of a preset sliding area in a first image, acquiring multiple sliding window results generated during the sliding process; determining the cutting position of the image to be processed based on the multiple sliding window results and the cutting position; determining whether the license plate to be recognized is a double-layer license plate based on the cutting position; if the license plate to be recognized is a double-layer license plate, cutting and stitching the image to be processed according to the cutting position to obtain a second image; and inputting the second image into a license plate recognition model to obtain a first recognition result. In this technical solution, the electronic device only needs to store a single-layer license plate recognition model to simultaneously recognize both single-layer and double-layer license plates, improving memory utilization and reducing the computing power used.

The application discloses a kind of based on image space random distribution lossless secret image steganography and extraction method, specifically is: using space technology in carrier image pixel low 4 place write secret information, the pixel value of secret image is using random sample to break up pixel order before embedding carrier image, for the embedding position of secret image in carrier image, using key generation random uniform distribution pixel position;Image extraction method, 16 bits character is extracted from the end of key, decode as the width and height value of secret image, through key generation secret image pixel position random sample and secret information embedding position in carrier image, extract secret information from embedding position, and restore each pixel of secret image, generate the secret image after restoration.The beneficial effects of the present application are: the present application can be used for covert information and the like Hidden transmission, with lossless extraction, embedding capacity is larger, information security is good, not easy to detect, the characteristics such as small consumption of computing power.

The invention provides a visual following method and system for an agricultural unmanned vehicle, a medium and an electronic terminal.The method comprises the steps that binocular images are collected through a binocular camera of the agricultural unmanned vehicle, and a human body frame is detected on a left eye image; two operation methods are adopted to realize following: one is based on a binocular distance measurement method, stereo matching and triangulation screening to obtain a following frame according with a preset adjustable following distance, and the other is based on the maximum-area human body frame as the following frame for following; according to the two operation methods, the following speed is adjusted through the area ratio of the current following frame to the previous following frame; according to the invention, the computing power is greatly saved, the response speed is increased, the operation efficiency is improved, the technical problems that the existing agricultural unmanned vehicle depends on manual remote control and the human-vehicle following scheme is insufficient to adapt to the agricultural scene are solved, real-time manual intervention is not needed, and the complex agricultural operation environment is efficiently adapted.

The utility model discloses a kind of waveform synthesis circuit and intermediate frequency electrotherapy instrument, waveform synthesis circuit includes: first amplitude adjusting circuit, with external controller connection, for the amplitude modulation processing of input waveform signal according to the overall amplitude adjusting signal from external controller, to obtain the first analog waveform signal after amplitude modulation;Second amplitude adjusting circuit, with the output end of external controller and first amplitude adjusting circuit connection, for the multiplication operation of modulated waveform signal and first analog waveform signal from external controller, to obtain the second analog waveform signal after amplitude modulation, and output second analog waveform signal and the inverse phase waveform signal of second analog waveform signal;Synthesis adjusting circuit, with the output end of external controller and second amplitude adjusting circuit connection, for the multiplication operation of fundamental frequency waveform signal and second analog waveform signal or the inverse phase waveform signal of this second analog waveform signal from external controller, to generate intermediate frequency treatment waveform.

The invention relates to a rare disease identification method and system based on multi-scale vision-language prompt multi-instance learning, and the method faces a full-view digital pathological image (WSI), and introduces the prior knowledge of the pathological field under the weak supervision condition of only using a slice-level label, so as to identify the rare disease. Constructing a multi-scale vision-language collaborative prompt mechanism: generating descriptive text prompts corresponding to image blocks of different scales by utilizing a large language model, designing a prototype-guided image block decoder to aggregate massive image block features, and meanwhile, realizing cross-modal alignment in combination with a context-guided text decoder; the method simulates the diagnosis process of a pathologist, achieves high-precision classification under small samples, remarkably improves the recognition accuracy of rare diseases, has good cross-center generalization ability, supports interpretable evidence output, does not need large-scale data labeling or de novo pre-training, and facilitates clinical rapid deployment.

This application discloses a method and apparatus for edge location detection, a self-moving device, a storage medium, and a program product. The edge location detection method includes: performing at least one region update operation during the movement of the self-moving device to update the target region; if a target region update is detected, updating the target map information to the attribute information of each first location point; if, based on the target map information, it is determined that among the multiple first location points, at least one target location point's height information conforms to a preset height range, determining the edge location based on at least one target location point. This method can reduce the storage space occupied by the self-moving device's map storage during edge location identification.

The application relates to the technical field of icing prediction, in particular to an icing weather time series prediction method and system based on a space-time generation network. The method comprises the following steps: an airborne terminal receives in-situ data; the airborne terminal performs a light compression and packaging operation on the in-situ data to generate a light file, and sends the light file to a ground terminal; wherein the following steps are included: denoising processing is performed on the in-situ data to obtain denoised data; the denoised data is compressed by using a target compression scale to make a light file; the ground terminal receives non-in-situ data; the ground terminal predicts a first icing probability of an airplane in a future period of time by using the non-in-situ data and the light file through a time series prediction model; and the ground terminal sends the icing probability to the airborne terminal. The application can greatly reduce the data fusion difficulty of a model input end.

The embodiment of the invention discloses a positioning method, a positioner and electronic equipment, and the positioning method comprises the steps: obtaining a plurality of satellite signals and an initial equipment position, screening out a reference non-line-of-sight signal and a reference line-of-sight signal from the plurality of satellite signals, and solving a reference elevation angle based on ephemeris information; controlling the array antenna assembly to perform dimension reduction resolving processing on the two-dimensional direction finding function based on the reference elevation angle to obtain a target azimuth angle; and correcting the initial equipment position based on the satellite position of the virtual satellite and the satellite position corresponding to the reference line-of-sight signal. According to the embodiment of the invention, the actual transmission path of the reference non-line-of-sight signals is restored through the reference elevation angle, the target azimuth angle and the reference pseudo-range, so that each reference non-line-of-sight signal becomes an effective positioning observed quantity, and the positioning precision is improved. According to the method, the characteristics of satellite signals are combined, the reference elevation angle calculated based on ephemeris information serves as priori knowledge, two-dimensional spectrum peak search is reduced to one-dimensional spectrum peak search, and calculation power is saved.

This application provides a charging device, a charging cloud platform, and a charging system. The charging device includes a temperature controller and a temperature sensor. The temperature sensor detects the temperature of the charging device, and the temperature controller adjusts the temperature of the charging device. The charging device is used to: transmit temperature control data during the output of DC power, including the temperature from the temperature sensor and the corresponding rotational speed of the temperature controller; receive an empirical temperature control curve, which is a curve showing the relationship between the temperature of the charging device and the rotational speed of the temperature controller. The empirical temperature control curve is fitted based on temperature control data from at least two charging devices, including the charging device itself and other charging devices besides the charging device; and control the rotational speed of the temperature controller based on the empirical temperature control curve and the temperature from the temperature sensor. The solution provided in this application can reduce the R&D investment in temperature control characteristics, thereby reducing economic and labor costs.

The application discloses a kind of frame structure building BIM three-dimensional model light weight processing method and system, it is related to image processing technical field, the method includes: obtaining target component grid to be processed and standard template grid, target component grid and standard template grid are carried out spatial pose alignment processing, and obtain alignment component grid;Geometric adaptation cropping processing is carried out to alignment component grid, and independent difference geometry is obtained;Parameter fitting is carried out to independent difference geometry, and hierarchical rendering instruction is obtained, hierarchical rendering instruction includes surface culling instruction and side wall filling instruction respectively generated for different plate thickness aperture of target component grid;Based on hierarchical rendering instruction, instantiation drawing processing is carried out to standard template grid, and the target model of rendering completion is obtained.The application achieves the technical effect of reconstructing high-fidelity model with physical thickness in the low-power environment of Web end.

This application provides a method, electronic device, and storage medium for retrieving information from table images. The method includes: using the table image as input to a text detection model to obtain the position information of text row candidate boxes output by the text detection model; identifying the strings contained within the text row candidate boxes using a text recognition model based on the position information of the text row candidate boxes; clustering the text content corresponding to each cell based on the position information of the text row candidate boxes corresponding to each string; calculating the matching degree between the received search statement and the text content corresponding to each cell based on the matching degree; and filtering out matching target text based on the matching degree. This solution only needs to identify the text content to complete the information retrieval from the table image, saving computing power, money, and time. It also solves the problems of inaccurate existing structured recognition methods, inability to recognize complex table types, and low universality.

The invention relates to the field of expressway safety, in particular to an expressway alarm event rechecking method and device, electronic equipment and a computer readable storage medium. The method comprises the steps that a plurality of alarm images corresponding to an alarm event are acquired, and the alarm images comprise target objects; obtaining motion feature description of the target object according to the plurality of alarm images, and constructing a re-checking prompt word according to the motion feature description; and inputting the re-checking prompt word and any alarm image into a multi-mode large model, and obtaining an alarm event re-checking result output by the multi-mode large model. According to the expressway alarm event rechecking method and device, the electronic equipment and the computer readable storage medium provided by the invention, the technical effects of improving the accuracy of an expressway alarm event rechecking result and reducing the expressway alarm event rechecking cost can be realized.

The application discloses an artificial intelligence silent evolution control system based on a fusible, contractible, auditable and interpretable edge protocol and belongs to the technical field of artificial intelligence system safety and reliability management. The system comprises an edge protocol bus, an interpretable module, a fusible module, a contractible module, an auditable module and a silent evolution management layer. The interpretable module calculates the confidence and the feature attribution path of the model output. The fusible module triggers the fuse according to the preset confidence condition and publishes an event. The contractible module executes dynamic resource contraction in response to the fuse event. The auditable module generates a three-tuple association log of the confidence, the fuse action and the contraction action. The edge protocol bus provides standardized event communication, module registration and version negotiation. The application solves the technical problems that the existing AI management module is isolated and cannot actively defend and heat evolve based on the output quality, and is suitable for high-risk AI application scenarios such as finance, medical treatment and automatic driving.

The present application relates to the field of image analysis, and particularly relates to an artificial intelligence identification method for urodynamic examination images. The present application obtains urodynamic contrast images and monitoring point displacement information, calculates a velocity time domain curve based on the displacement information, and captures a steady state time period. The present application positions a key contrast frame through time sequence alignment, selects adjacent continuous frames to construct a reference frame group through a sliding window, identifies a reference frame group organization contour to generate a superimposed thermal map, determines a superimposed main contour through frequency threshold screening and contour closure processing, calculates the interval width perpendicular to the contour based on displacement extreme values, constructs a strip-shaped dynamic reference interval along the main contour, and performs local enhancement on the images in the tissue contour reference interval. The present application specifically considers dynamic interference caused by physiological movement, improves the key area development quality, improves the image processing efficiency, and helps doctors to improve the diagnosis speed and efficiency.

The present application relates to a kind of signal wave direction and modulation pattern combined intelligent estimation model construction method, belong to signal analysis processing technical field, solve the existing technology in the wave direction estimation and modulation pattern identification, there is the problems of algorithm complexity, high hardware cost etc..The present application is by constructing multi-task deep neural network structure, and collecting multiple synchronous sampling IQ data stream, forms training sample and test sample, trains neural network structure, and increases modulation pattern and wave direction estimation extraction module, obtains wave direction and modulation pattern combined intelligent estimation model, then estimates test sample, obtains wave direction estimation result and modulation pattern identification result, completes the construction of model.Realize with less performance loss while realizing higher precision wave direction estimation and higher accuracy modulation pattern identification, it is favorable to reduce the workload required for the correlation of two kinds of results, while the demand for processing equipment algorithm can be reduced.

This invention discloses a low-light image enhancement method based on random region concealment and reconstruction. The network consists of two stages. In the first stage, the network is trained on a well-lit image dataset to reconstruct the noisy image after random regions are concealed, resulting in a denoising and reconstruction feature encoder for low-light noisy images. In the second stage, the network inherits the feature encoder model parameters from the first stage and inputs the extracted different features into a multi-scale feature fusion module guided by the reconstructed features. This allows the network to retain more image detail features while denoising. This invention utilizes a richer dataset of well-lit images, saving time and manpower by capturing a large number of real paired low-light images for network training. By fusing features extracted from different feature encoders, the network can quickly adapt to real low-light images under complex lighting conditions, achieving good low-light enhancement and denoising effects.

The application discloses an electric equipment cooperative control method and system, and relates to the technical field of unmanned ship control; the technical points are as follows: through space-time-electromagnetic double-dimension synchronous preprocessing, taking the geomagnetic detection sampling time sequence as a core reference, the phase reference alignment of the power supply time sequence, the equipment operation time sequence and the detection sampling time sequence is carried out, so that the electric interference peak value is avoided from falling into the detection sampling window; in addition, on the basis, through matching the cooperative control decision value, three cooperative operations of power supply ripple reverse offset, equipment time sequence and detection window avoidance, and ship body posture and detection sampling phase lock are executed, active offset and accurate avoidance of electromagnetic interference are carried out from the power supply source, equipment operation and detection sampling, the problem that the prior art can only realize passive interference attenuation through physical isolation and hardware shielding, and cannot eliminate the interference source through electric cooperative control is solved, and thus the electromagnetic interference suppression efficiency of the geomagnetic detection channel and the signal-to-noise ratio of the geomagnetic detection data are improved.

This application discloses a multi-path, multi-packet matching and fusion method based on loopback segmentation judgment, belonging to the field of map data processing. The method includes acquiring multiple low-precision map packets from the same task; determining whether each low-precision map packet contains backtracking paths and segmenting backtracking paths to obtain low-precision single-packet maps; in each low-precision single-packet map, generating a corresponding sub-map with a fixed range, using randomly selected data elements as center points; simultaneously performing feature extraction and automatic matching on the two sub-maps corresponding to each center point of every two adjacent low-precision single-packet maps to obtain matching scores for different data elements between the two sub-maps; and determining the object corresponding to the most certain match that meets geometric consistency based on the matching scores. This application can save equipment costs, overcome the reliance on the uniqueness of map elements in existing technologies, and the established low-precision single-packet maps facilitate subsequent matching.

The invention relates to computing (S101) an information content of a section of a current image of a series of images of a video signal, wherein the video signal has to be fed to an algorithm for computing and indicating a detection of an object in the video signal. If the computed information content of the section of the current image is less than a threshold (S103), the computing and indicating of the detection of an object of the section of at least the current image or of the current image and further images of the series of images is suppressed (S105).

The invention discloses a point cloud noise filtering method and device and related equipment, and the method comprises the steps: carrying out the downsampling of first point cloud data, obtaining second point cloud data, and enabling a laser radar to detect a target region to obtain the first point cloud data; screening out a candidate noise point cloud set from the second point cloud data, the distance of each point cloud in the candidate noise point cloud set being within a preset distance range, and the reflection intensity of each point cloud being within a preset first intensity range; based on the number of point clouds in each voxel of a point cloud grid, the position of each point cloud and the reflection intensity, whether each point cloud in the voxel is noise is judged, and the point cloud grid is generated based on each point cloud in the candidate noise point cloud set; and rejecting point clouds which are judged to be noise from the candidate noise point cloud set to obtain target point cloud data. According to the invention, miscellaneous points received by the eVTOL during vertical take-off and landing and low-altitude flight can be effectively filtered, and the stability of obstacle recognition is improved.

The application relates to the technical field of intelligent household appliances, and discloses a cross-domain small sample object image classification method and device for an intelligent terminal, which comprises the following steps: obtaining an object image to be identified; processing the object image to be identified by using a feature extraction module to extract a basic feature vector; processing and fusing the basic feature vector by using a double Riemann manifold processing module to generate a comprehensive feature representation; outputting an object classification recognition result by processing based on the comprehensive feature representation through a classification layer; the feature extraction module, the double Riemann manifold processing module and the classification layer constitute a lightweight self-network model; the lightweight self-network model is obtained by removing a teacher network after joint training through topological relationship knowledge distillation and progressive self-training. The lightweight self-network obtained by the method is suitable for the low computing power and low storage requirement of an intelligent terminal edge end, can realize local low-delay and high-precision classification and recognition of an object image, and solves problems such as uneven illumination and domain offset in the intelligent terminal.

The present invention provides a multi-modal obstacle avoidance system for multi-sensor fusion of an unmanned ship based on ROS, which is characterized by including three parts: sensors, a controller, and an actuator. In this system, a lidar, an industrial camera, an inertial measurement unit, and a GPS module are used to sense the surrounding environment and obtain attitude and position information, belonging to the sensors of the system; an artificial intelligence development board and a single-chip microcomputer are the main control modules, which make decisions according to the input through built-in algorithms, belonging to the controller of the system; a drive controller and a drive mechanical device are used to execute the decisions of the controller, belonging to the actuator of the system; the present invention uses a multi-sensor distributed modular architecture, enabling various functions to be coupled together, allowing tasks to be executed simultaneously in multiple threads, greatly reducing computing power, making the control more flexible, and equipped with a high-efficiency and high-accuracy vision-lidar fusion obstacle avoidance algorithm, enabling the unmanned ship to flexibly handle various complex situations that occur on the water surface and having the capabilities of autonomous cruising and autonomous obstacle avoidance.

The present disclosure relates to a vehicle body roll swing control method, a controller, a vehicle and a storage medium. The vehicle body roll swing control method comprises: obtaining an excitation frequency of a vehicle running road surface; determining a target preset frequency band corresponding to the excitation frequency, and a target preset corresponding relationship corresponding to the target preset frequency band, wherein the target preset corresponding relationship is a corresponding relationship between the excitation frequency of the road surface and the current of the shock absorber, different target preset frequency bands correspond to different target preset corresponding relationships; and adjusting the current of the shock absorber according to the excitation frequency and the target preset corresponding relationship to adjust the damping of the shock absorber. The technical solution provided by the present disclosure uses only the target preset corresponding relationship between the road surface excitation frequency and the current of the shock absorber to adjust the current of the shock absorber according to the road surface excitation frequency, realizes the control of the vehicle body swing and good vibration isolation performance, and the algorithm is simple and saves computing power.

The present application relates to the field of offshore oil spill detection, especially to an adaptive offshore oil spill detection method, the present application extracts the marine environment features in the inspection image, and then analyzes the time domain changes of the marine environment features, constructs the time domain change curve of marine texture distribution features and the time domain change curve of image attribute features, and then verifies the index dispersion constraint and index mutation constraint of each curve segment, sets a label for the inspection image, determines the optimal verification perspective for the inspection image with the set label, and captures the drift feature to set a potential oil spill label under the optimal verification perspective, the present application saves the computing power for image analysis by using the change of marine environment features when large-area sea area is inspected at night, finds the optimal verification perspective of the highlighted features in the verification image under the environmental light interference by shifting the background through the optimal verification perspective, and improves the reliability of oil spill detection in large-area sea area at night through dynamic perspective selection and drift verification.