32results about How to "No need for manual identification" patented technology

The invention provides a method and a device for collecting malicious software automatically, wherein the method comprises the following steps: S1, scanning web pages through a simulative browser, identifying and capturing a malicious code of the scanned web pages; and S2, constructing a malicious code executing environment to capture the malicious code so as to obtain the malicious software. The method can realize to collect the malicious software automatically without manual identification; therefore, efficiency is increased greatly; in addition, the method starts to identify the malicious code so as to obtain the malicious software without a method of collecting the static characteristics of the malicious software; the malicious software including the malicious code can be collected no matter the malicious software uses deformation methods; and reliability and relevance ratio are improved greatly.

The invention discloses a method and device for identifying phishing websites and aims to solve the problem that efficiency and accuracy in identifying phishing websites by the prior art is low. The method includes: using a URL (uniform resource locator) in information of interaction between a terminal and a network side and a URL embedded in a page in preset page type as URLs to be identified; when first similarity between the URLs to be identified and a set URL is within a set range, identifying the URLs to be identified as URLs of phishing websites. Whether the URLs to be identified are the URLs of phishing websites or not is determined according to the first similarity between the URLs to be identified and the set URL, the method for automatically identifying phishing websites is realized, and the efficiency in identifying phishing websites is improved. The URL embedded in the page in the set page type is used as the URL to be identified for identification, so that accuracy in identifying phishing websites is improved.

The invention relates to a nondestructive detection method for weld defects based on computer vision, which comprises the following steps of carrying out semantic segmentation on a weld x-ray negative film to obtain a weld edge, and carrying out connected domain analysis on an inner side area of the weld edge to obtain a connected domain on the inner side of the weld; segmenting the edge of each connected domain to obtain an outer edge close to one side of the base material and an inner edge close to one side of the center of the welding seam; respectively obtaining the identification degree, the blackness and the straightness of the inner edge and the outer edge; obtaining the definition of the inner edge and the outer edge by using the identification degree and the blackness; obtaining a non-fusion rate of the connected domain according to a definition difference value and a straightness difference value between the inner edge and the outer edge; and setting a threshold value, comparing the threshold value with the non-fusion rate corresponding to the connected domain, and marking the connected domain according to a comparison result of the threshold value and the non-fusion rate corresponding to the connected domain. According to the technical means provided by the invention, the non-fusion defect of the welding seam can be accurately identified, and the easy-to-confuse type identification of the welding seam defect is more accurate.

The invention relates to the technical field of user portraying, and provides a federation model training method and device, a customer portraying method and device, equipment and a medium, and the method comprises the steps: obtaining a participant list and an initial customer portraying federation model, and screening out qualified participants from the participant list according to a preset screening scheme; sending the initial customer portrait federation model to each qualified participant; receiving returned model parameters; performing abnormal feature extraction through a malicious parameter detection model by applying an MPI parallel method, and outputting an identification result of each model parameter according to the extracted abnormal features; filtering malicious parameters to obtain final normal parameters; and performing updating and federation learning to obtain a global customer portrait federation model. According to the method, the MPI parallel method is applied, abnormal feature extraction and malicious parameter filtering processing are carried out through the malicious parameter detection model, malicious parameters provided by malicious participants are automatically removed, and the efficiency and precision of federal learning modeling are improved.

The invention discloses a webpage horse hanging identification method and system. The method comprises the steps of obtaining a URL of a to-be-detected website; pushing the URL to be detected to a virtual machine sandbox, wherein a horse hanging detection and verification system is arranged in the sand box; carrying out simulation access on the URL to be detected by adopting a simulation browser in the horse hanging detection and verification system, and analyzing the received response content; judging whether the analyzed response content has content which is the same as or similar to the first set label or not, wherein the first set label is a preset keyword; if so, giving an alarm; determining the content of which the relevancy with a second set label is greater than a preset value in the analyzed response content, and recording the content as suspicious response content, wherein the second set label comprises a horse hanging label; executing the suspicious response content in the sandbox by adopting a simulation browser; and matching the execution result with a preset verification rule for detecting the horse hanging behavior, and if matching succeeds, giving an alarm. The method has the advantage of high horse hanging identification efficiency.

The invention relates to the technical field of image fusion, in particular to an ultraviolet image corona recognition and positioning method and system based on image fusion. According to the invention, when the visible light image and the ultraviolet image are collected, the resolution of the visible light image and the resolution of the ultraviolet image are ensured to be the same, so that the conditions are the same when enhancement and gray processing are carried out later, the system error is reduced, and the fusion precision is improved. According to the method, the equipment on the visible light image is matched with the equipment in the database, which equipment generates corona can be automatically identified without manual identification, and the method can be associated with a rear-end monitoring system to give a prompt about which equipment generates corona. Equipment templates in the database comprise insulation equipment image templates such as a transformer image template and an insulator image template.

The invention discloses an ultrasonic image processing method and system, and belongs to the field of data management. The ultrasonic image processing method comprises the following steps that to-be-processed ultrasonic data sent by a client is distributed to a processing node server in a cloud computing platform meeting a preset condition; the processing node server analyzes the to-be-processed ultrasonic data, obtains the ultrasonic analysis data and sends the ultrasonic analysis data to the corresponding client, so that the purpose of automatically identifying the ultrasonic data is achieved, manual identification is not needed, and the condition of missed diagnosis is avoided. Meanwhile, the cloud computing platform is adopted for ultrasonic data analysis, so that the calculated amountof local equipment (such as ultrasonic equipment, workstations or PACS of hospitals and the like) is reduced.

The invention provides a corn plant type identification method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a field corn plant image, and obtaining an edge image based on the field corn plant image; based on the edge image, disconnecting an annular path of the edge image to obtain an initial path set; removing multi-path connection points corresponding to the field corn plant image based on the initial path set to obtain a path endpoint set; performing quadratic curve fitting on every two endpoints in the path endpoint set in pairs to obtain a target path set; and based on the target path set, determining an included angle between the center line of the corn stalk and the corn vein fitting straight line, and based on the included angle, determining the corn plant type. According to the method provided by the invention, the corn plant type can be automatically judged through the field corn plant image, manual identification is not needed, the plant type data acquisition efficiency and the accuracy of corn plant type judgment are greatly improved, and a support is provided for variety evaluation automation and commercial breeding development.

The invention relates to a park garbage monitoring system based on a LoRa Wide Area Network (LoRaWAN). The system comprises a central processing unit (CPU), wherein the CPU is electrically connected with both a garbage monitoring system and an alarm system through a LoRa gateway; the garbage monitoring system comprises infrared sensors, cameras, a switch group and garbage identifiers, which are all electrically connected with the CPU; the switch group comprises switches which are respectively connected with recyclable garbage bins, snack garbage bins, harmful garbage bins and other garbage bins; and the alarm system comprises buzzers, display screens and alarm lights which are all electrically connected with the CPU. Therefore, the system provided by the invention has the advantages that garbage can be accurately treated, and the garbage amount can be more effectively monitored.

According to the electrocardiogram artifact analysis method based on the optimal scoring strategy, electrocardiogram artifacts with short duration caused by poor electrode contact, muscle vibration and movement interference introduced in activities can be automatically recognized, and the working efficiency of technicians is greatly improved. According to the technical scheme, the feature inflection points are found in the heart beat sample to be analyzed, the feature inflection points with the features of the Q point, the S point, the T starting point and the T ending point are found in all the feature inflection points, and the feature inflection points which do not conform to the QST combination position features are deleted. All feature inflection point combinations strictly conforming to the features between the Q point and the S point, the features between the S point and the T point and the features between the T starting point and the T ending point at the same time are found, and finally based on feature parameters such as the sharp incisura number of each combination, scoring is conducted through a scoring function, and the electrocardiograph artifacts are found.

The invention discloses a blood vessel detection method, ultrasonic equipment, and a computer-readable storage medium. The blood vessel detection method comprises the following steps: determining a target blood vessel area of an ultrasonic image; obtaining a maximum blood vessel diameter and a minimum blood vessel diameter corresponding to the target blood vessel area; determining a blood vessel stenosis ratio of the target blood vessel area according to the maximum blood vessel diameter and the minimum blood vessel diameter. According to the blood vessel detection method provided by the invention, on one hand, blood vessel stenosis analysis can be automatically carried out on a target blood vessel area, manual identification of the blood vessel stenosis condition is not needed, and time and labor are saved; on the other hand, the blood vessel stenosis can be quantitatively analyzed, and the blood vessel stenosis condition can be more accurately judged.

The invention discloses a hair blowing device for cloth. The hair blowing device comprises a workbench, a vertical plate is arranged on each of left and right sides of the workbench, a sliding block which slides is arranged at the upper end of each vertical plate, an air blowing adjustment box is arranged between the two sliders, comprises an air distribution cavity positioned at an air inlet andan air feeding cavity positioned at an air outlet and blows air to the cloth on the workbench, and a lower guide groove is formed in the lower end of each sliding block and slides along the corresponding vertical plate. Moving of the air blowing adjustment box is realized through the sliding blocks sliding along the vertical plates, and whole-size air blowing of the cloth on the workbench is realized through the air blowing adjustment box; the air distribution cavity and the air feeding cavity are communicated through a connection air groove; through the opposite arc-shaped structure of an inverted ventilation cover and an upper cover plate, uniform air distribution is realized, and the problem that uniform air outgoing cannot be realized due to excessive transverse length is solved thoroughly. Air can be blown to the cloth conveniently, and manual thread end recognition is not needed.