12results about How to "Fully characterized" patented technology

The invention discloses a multi-source ship target identification method based on two-stage collaborative fusion, and relates to the technical field of signal processing, and the method comprises the steps: firstly collecting target sea area data, including original optical image and radar image data, by means of an optical camera and a radar sensor on an aircraft, and then carrying out the preprocessing of the collected data through Gaussian filtering; performing sea-land segmentation by using a deep learning algorithm, constructing a loss function optimization network parameter to obtain a segmentation mask, and removing a land background area according to a mask result to obtain processed optical and radar images; an improved SURF feature and graph cut algorithm combined registration method is adopted, optimal transformation parameters are obtained by screening feature point pairs and solving the minimum value of an energy function, and image registration is achieved; for the registered images, fusing the images based on an adaptive fusion rule; and finally, extracting corresponding features through manual feature extraction and feature extraction based on deep learning, and fusing the features to obtain a final target recognition result.

The invention discloses a flue-cured tobacco maturity classification method and device, and relates to the technical field of flue-cured tobacco classification. The method comprises the following steps: respectively manufacturing upper, middle and lower flue-cured tobacco maturity samples by a tobacco leaf grading expert, acquiring spectral data of the flue-cured tobacco maturity by an imaging system, and eliminating noise in the spectral data of the flue-cured tobacco maturity by using a moving average filtering method and a multivariate scatter correction method; the method comprises the following steps: integrating a spider bee intelligent optimization algorithm into a 1D-ResNet model to establish an SWO-ResNet model, using SWO to intelligently optimize batchsize and epochs parameters in the 1D-ResNet model, using the SWO-ResNet model to extract a spectral characteristic wave band of flue-cured tobacco maturity, and using an LDA classifier to establish a flue-cured tobacco maturity classification model. The flue-cured tobacco maturity classification method capable of being described is established, and classification of the flue-cured tobacco maturity is completed through spectral characteristics.

The present invention discloses a memory failure early warning method and device, which relates to the field of computer technology. The main purpose of the present invention is to describe the characteristics corresponding to the memory working state from multiple dimensions, so as to predict whether the memory has a failure risk. The main technical scheme of the present invention is: obtaining the abnormal log of the device; analyzing the time series change characteristics of the memory abnormal log according to a preset time period based on the memory abnormal log in the abnormal log; counting the operating state characteristics of the memory in the device based on the address information of the memory error in the abnormal log; fusing the time series change characteristics with the operating state characteristics into a memory failure early warning feature; using the early warning model to process the memory failure early warning feature to obtain the memory early warning information of the device.

The invention discloses a data acquisition method and system for a digital model, and relates to the technical field of data acquisition, and the method comprises the steps: recognizing a redundant field based on the uniqueness of the field, and determining the redundancy and threshold of system security alarm data; preprocessing the system security alarm data, and constructing node variable characteristics of the preprocessed system security alarm data; and constructing an acquisition model based on the node variable characteristics and the system security alarm data. According to the method, the redundant field is identified based on the uniqueness of the field, and the field of the system security alarm data is analyzed by using the first normal form principle, so that the accuracy of redundancy identification is improved, the accurate quantification of the data redundancy is realized, and the accuracy of the system security alarm data is improved by preprocessing the system security alarm data. The method improves the quality and consistency of system security alarm data, and provides a more comprehensive feature description for the analysis and modeling of the relationship between complex data through distribution feature function extraction and matrix processing.

The invention relates to the technical field of video data analysis and processing, and discloses a video data-based artificial information checking, collecting and early warning method, which comprises the following steps of: S1, collecting video data from cameras mounted at different positions through an identification system; s2, preprocessing the collected video; s3, key features of the preprocessed video are extracted; a predetermined risk area and different types of predetermined transaction areas are divided based on a scene view, risk areas are dynamically divided according to historical data and a real-time monitoring result, key monitoring is performed on a high-risk area, the pertinence and effectiveness of risk management are improved, manual information check and collection are performed on behavior tracks with scores higher than a predetermined threshold, and the risk management efficiency is improved. And the result is fed back to the system in time, and subsequent analysis and early warning are adjusted and optimized, so that the intelligent level and accuracy of the early warning system are improved, the overall safety and reliability of the monitoring system are improved, and potential safety risks are effectively prevented and processed.

The embodiment of the invention discloses a commodity marking method and device, electronic equipment and a storage medium, and relates to the technical field of commodity display, and the method comprises the steps: obtaining multi-modal commodity information of a game commodity object; performing feature extraction on the multi-modal commodity information to obtain commodity features of the game commodity object, and performing feature combination according to the commodity features to obtain combined features of the game commodity object; and marking the game commodity object according to the commodity characteristics and the combined characteristics to obtain a plurality of selling point labels for the game commodity object.

The embodiment of the invention provides a tomato maturity prediction method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring a color image, one-dimensional near infrared spectrum data and one-dimensional ultrasonic spectrum data of a tomato; performing feature extraction on the color image to obtain a visual feature vector; converting the one-dimensional near infrared spectrum data into two-dimensional near infrared spectrum data, and performing feature extraction on the two-dimensional near infrared spectrum data to obtain a near infrared spectrum feature vector; performing feature extraction on the one-dimensional ultrasonic spectrum data to obtain an ultrasonic feature vector; based on an attention mechanism, performing feature fusion on the visual feature vector, the near infrared spectrum feature vector and the ultrasonic feature vector to obtain a target fusion feature vector; and predicting the target fusion feature vector to obtain the maturity. According to the invention, the accuracy of tomato maturity prediction is improved.

A method for fault diagnosis of on-load tap changers based on phase space reconstruction theory, in the technical field of fault diagnosis of on-load tap changers, is used to solve the problem that wavelet analysis and modal decomposition methods focus on time domain or frequency domain features, lack in-depth analysis of the overall spatial characteristics and complex structures of signals, and thus their recognition capabilities are limited when faced with complex fault modes. Aiming at the fault diagnosis and identification problems of KM type oil-immersed online transformer tap changers OLTC, the present invention adopts vibration signal analysis, feature extraction and machine learning technology, and proposes an effective fault classification method to improve the reliability and operation efficiency of the equipment. CatBoost is selected as the fault classification model, and the hyperparameters are systematically adjusted using Bayesian optimization to obtain the optimal hyperparameter configuration. This process significantly improves the classification accuracy of the model and enhances its robustness.

The present application discloses an object recommendation method, device, electronic device and storage medium, belonging to the field of Internet technology, the method comprising: when the object recommendation condition of the target account is met, obtaining at least one candidate object, performing feature analysis based on the nodes in the constructed knowledge graph that have a connection relationship with the nodes corresponding to each candidate object, obtaining feature description information of the candidate object, performing interest analysis based on the path information between the node corresponding to the historical interaction object of the target account in the knowledge graph and the node corresponding to the candidate object, obtaining the target account's interest information on the candidate object, matching the feature description information of the candidate object with the target account's interest information on the candidate object, and performing object recommendation based on the matching results of each candidate object and the target account. In this way, the feature description of the candidate object is more comprehensive, and the target account's interest analysis on the candidate object is more accurate, so the recommendation accuracy is higher.

The application discloses a kind of molecular modeling method and modeling system based on electron density, wherein the method comprises: obtaining atomic coordinate information in target molecule;Based on atomic coordinate information, electron density grid point information of target molecule is obtained at preset resolution;From electron density grid point information, target electron density value greater than preset electron density value is extracted, and 3-dimensional matrix formed by target electron density value is constructed as the molecular model of target molecule.The technical scheme provided by the application solves the problem that the features contained in the traditional molecular representation model are insufficient.

This application is applicable to the field of terminal technologies, and in particular, to an artificial intelligence (Artificial Intelligence, AI) terminal-based screenshot display method and apparatus, and a terminal device. The screenshot display method is applied to a terminal device having a foldable screen. The foldable screen includes a first display and a second display. The screenshot display method includes: obtaining a first included angle between the first display and the second display; performing a screen capturing operation on current display content of each of the first display and the second display, to obtain a first screenshot corresponding to the first display and a second screenshot corresponding to the second display; and displaying the first screenshot and the second screenshot based on the first included angle. The first included angle between the first display and the second display is obtained during screen capturing, so that three-dimensional display of the first screenshot and the second screenshot can be performed based on the first included angle, to fully reflect foldable and bendable characteristics of the terminal device having a foldable screen, and improve a display effect of the screenshots.