42results about How to "Avoid identification" patented technology

The invention provides a crane hoisting monitoring method and system based on multi-normal-form visual fusion and a medium, and relates to the technical field of computer vision. Acquiring an image of the target acquisition area through an image acquisition device, and obtaining a real-time image acquisition video stream; preprocessing the real-time image acquisition video stream to obtain real-time image frame data; performing real-time image frame data identification based on the visual detection model to generate detection information; inputting the detection information into a visual tracking module, and tracking the identification object to obtain tracking information; acquiring a fixed dangerous area or a dynamic dangerous area based on the detection information and the tracking information; and identifying a dangerous condition in the video stream according to the dynamic dangerous area or the fixed dangerous area, obtaining dangerous condition accumulated data and triggering an alarm. The technical problems that in the prior art, the monitoring means is single, and dynamic dangers are difficult to accurately recognize are solved, and the technical effect of accurately recognizing potential dangers of hoisting operation in real time is achieved.

The invention discloses a power transmission line unmanned aerial vehicle inspection picture defect identification method and system. The method comprises the following steps: carrying out picture resolution amplification processing on a power transmission line unmanned aerial vehicle inspection picture; inputting the processed picture into a large target component identification model, identifying large target component defects and large target components where small target component defects are located, obtaining confidence coefficients corresponding to the identified large target component defects, and retaining each identified large target component defect greater than a confidence coefficient threshold value; cutting an image of the large target part where the identified small target part defects are located, inputting the image into a small target part identification model, identifying the small target part defects, obtaining confidence coefficients corresponding to the small target part defects, and retaining each identified small target part defect greater than a confidence coefficient threshold value; and summarizing the recognized defects of the large target part and the recognized defects of the small target part, and outputting a defect recognition result. According to the method and the device, the problem of defect identification of images with high resolution and concentrated defect distribution can be solved.

The invention relates to a block chain transaction method supporting privacy protection and identity tracking, and belongs to the technical field of block chain application. The specific process of the method is as follows: a financial management institution FMA generates a public key / private key pair for member registration and anomaly analysis according to a security parameter lambda, and group sending is performed on public keys; deploying a recharging contract and a payment contract on the block chain; each consumer ui registers to the FMA through a mobile device to become a member user of the transaction system, and the consumer holds a group signature key gski returned by the FMA after successful registration; the payment service operator cj registers to the FMA to become a member before providing service, and after successful registration, the payment service operator holds the FMA to return an identifier pid of each product terminal managed by the payment service operator; and the consumer calls a payment contract to carry out order payment based on the signature key gski and the identifier pid of the product terminal, and finally, the method further comprises an anomaly analysis link.

The invention relates to the technical field of micro-droplet detection, solves the technical problem that in the prior art, micro-droplets in multiple working condition states cannot be accurately recognized, and particularly relates to a color feature-based micro-droplet image recognition method and a micro-droplet observation device. The micro-droplet image recognition method comprises the following steps: acquiring video image data of a micro-channel in a micro-fluidic chip in an optimal visual field of a color high-speed industrial camera, and converting the video image data into an HSV color space to obtain color images of micro-droplets with different color features; and judging the attribution of the segmented region according to the area of the micro-droplet region and the characteristics of the approximate circle. According to the method, searching and positioning can be carried out based on the color features of the micro-droplets, good robustness is achieved for other complex non-target edge features such as noise, shielding and bubbles, even multiple targets with similar shapes and areas can be accurately recognized, and the method can be well suitable for multi-channel color images.

The invention provides an unmanned aerial vehicle flight path planning method and system under a flight path deception interference background, and belongs to the field of unmanned aerial vehicle flight path planning, and the method comprises the steps: setting an unmanned aerial vehicle flight speed range, an unmanned aerial vehicle flight height, an unmanned aerial vehicle maximum turning rate and an unmanned aerial vehicle maximum climbing angle, and building constraint conditions; weighting the total energy consumption of unmanned aerial vehicle motion, the total channel transmission loss of communication signals between the unmanned aerial vehicles and the radar discovery probability, and constructing an evaluation function model; and generating a false track of deception jamming according to a task demand, selecting a distance ratio coefficient as a particle of PSO, outputting an optimal fitness value and a corresponding particle position in combination with a constraint condition, and obtaining an unmanned aerial vehicle track planning result. The radar discovery rate and the transmission loss of the obtained unmanned aerial vehicle flight path planning result are optimal, and preconditions and reliable guarantee are provided for implementation of flight path deception interference.

The invention discloses an alarm information processing method and device and a nonvolatile storage medium. The method comprises the following steps: acquiring alarm information generated by a plurality of alarm devices, and classifying the alarm information according to the types of the alarm devices; target alarm information corresponding to each type of alarm equipment is collected based on the time sliding window, and the target alarm information is alarm information corresponding to the time range indicated by the time sliding window; based on the topological relation between the target alarm information and the network equipment, a causal graph is constructed, and the causal graph is used for indicating the causal relation of information propagation between the target alarm information; and determining key alarm information based on the causal graph. The technical problem of low processing efficiency caused by incapability of accurately identifying key alarm information of multiple pieces of alarm information due to neglect of a causal relationship between the alarm information in related technologies is solved.

The embodiment of the invention provides an attack resisting method and device, equipment and a storage medium. The method comprises the following steps: acquiring an initial image, and dividing the initial image into a plurality of panes according to a preset window size; in response to the fact that the pane is covered by the prompt, determining the pane covered by the prompt as a target pane; an initial confrontation sample is optimized based on the target pane, so that disturbance generated by the initial confrontation sample is not higher than a disturbance threshold value, the optimized target confrontation sample is output, and the initial confrontation sample is generated by adding noise to the initial image. And using the target confrontation sample to attack an image segmentation model to obtain an attack result, the image segmentation model comprising an image encoder, a prompt encoder and a mask encoder. The embodiment of the invention aims to improve the generalization ability and success rate of attack resistance.

This invention relates to an active learning-based data-free black-box attack method and system based on multidimensional value assessment, belonging to the field of artificial intelligence security technology. This method constructs a pre-emptive "sample screening funnel," utilizing a local substitution model to perform multidimensional assessments of sample boundary approximation, information uncertainty, and geometric diversity before sending images to a commercial cloud API. Only high-value samples are selected for querying, thereby achieving low-cost, high-efficiency model theft and adversarial attacks. This invention ensures the diversity and training stability of data-free generated samples, significantly improves the transfer success rate of adversarial examples, and achieves "low-cost, low-risk" economical attacks. It has strong versatility and can be seamlessly integrated into various existing data-free attack frameworks, facilitating deployment and implementation in practical security assessment systems.

The present invention proposes an image DCT steganography optimization method based on reinforcement learning, which relates to the field of image processing and information hiding technology. By dynamically selecting appropriate image blocks in the discrete cosine transform (DCT) domain for steganographic operation, the security of information embedding and image quality are optimized. The method first divides the image into several DCT coefficient blocks, and constructs a strategy network for image blocks in different regions. According to the DCT coefficients, energy distribution and image quality indicators of each image block, the system state is constructed, and the DCT coefficient embedding block for the steganographic operation is dynamically selected using a hierarchical reinforcement learning algorithm. While ensuring the image quality, it can not only make the embedded information more concealed, but also effectively avoid being easily identified in conventional detection algorithms.

The invention provides a millimeter wave radar system based on an underground mine tunnel and a vehicle auxiliary system. The radar system is characterized in that a radar radio frequency front-end circuit comprises a plurality of cascaded millimeter wave radar chips which are connected with a data acquisition and processing module through a serial peripheral interface, and the plurality of cascaded millimeter wave radar chips are divided into a master chip and at least one slave chip; local oscillation signals generated by the master chip are distributed to the slave chip through the Wilkinson power divider, a digital frame synchronization clock is distributed to the slave chip through the master chip and the clock distributor, and original ADC data captured by the millimeter wave radar chips are transmitted to the data acquisition and processing module. And the data acquisition and processing module is used for performing multi-dimensional FFT processing on the original ADC data transmitted by the radar radio frequency front-end circuit to obtain a distance Doppler image, and separating and identifying a distance and speed map in the distance Doppler image through a CFAR algorithm to obtain distance and speed information of each target around and in the roadway.

The utility model relates to the technical field of landscape elevator security and protection, and particularly discloses a security and protection system for a suspension bridge main tower attached landscape elevator, which comprises a waiting channel, a ticket checking gate, a camera and a weighing platform, the waiting channel is arranged at an elevator doorway, the camera is arranged above the waiting channel, and the camera is connected with an image recognition module and is used for recognizing the number of people in the waiting channel; the ticket checking gate machine is installed at an entrance of a waiting channel and connected with the controller, the controller controls the ticket checking gate machine to open or close ticket checking, a weighing table is arranged at the entrance of the ticket checking gate machine and measures the weight of a ticket checker, and a mass sensor is arranged below the weighing table and connected with a calculation module. The calculation module and the image recognition module are both connected with the controller, the controller controls the ticket checking gate to be opened or closed for ticket checking according to the weight collected by the mass sensor and the number of people recognized by the image recognition module, the number of people entering the elevator and the weight of people entering the elevator are accurately controlled, and overload of the elevator is effectively prevented.

The invention discloses a data frame detection circuit and a data frame detection method for a communication system. The circuit comprises a preorder code detection unit and a shielding unit. The preamble code detection unit is used for detecting a preamble sequence code in a data frame and generating a first enable signal based on the preamble sequence code; the shielding unit generates a shielding control signal with a shielding window based on a first enable signal and a reference clock signal, closes the preorder code detection circuit based on the shielding window of the shielding control signal, and opens the preorder code detection circuit after the shielding window ends. According to the data frame detection circuit and the data frame detection method for the communication system, shielding window protection is provided after system initialization is finished, and the preorder code detection unit stops receiving the data frame during the effective period of the shielding window, so that the situation that error data caused by any reason triggers preorder code identification and interferes normal work of a link is prevented; the problem of sensitivity to EMC in the link establishment process is solved.

The invention relates to a cloud honeypot camouflage implementation method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps of obtaining a target probe bound with a cloud honeypot, performing access monitoring based on the target probe to obtain the target probe bound with the cloud honeypot, and performing access monitoring based on the target probe; under the condition that an access object is monitored through the target probe, acquiring a command input by the access object; the original execution logic of the command is updated based on the cloud honeypot to obtain updated execution logic, and the updated execution logic is used for enabling an execution result obtained by executing the command to be the same as an execution result obtained by accessing a real server environment by the access object; and executing the command according to the update execution logic to obtain an execution result, and feeding back the execution result to the access object. By adopting the method, the honeypot can be prevented from being identified by the access object, and the effect of disguising the access object is achieved.

The invention discloses a data hiding method and device, a data processing method and device and electronic equipment. Relates to the technical field of networks, and comprises the following steps: obtaining to-be-hidden data, and performing data processing on the to-be-hidden data to obtain target data, the target data being different from the to-be-hidden data, and the target data being used for restoring the to-be-hidden data based on an inverse processing mode of data processing; a target folder in the target storage area is named based on the target data, and the naming of the target folder is used for enabling the to-be-hidden data to bypass file detection. According to the data hiding method and device, the technical problem that the data hiding reliability is low due to the fact that a file is generated in the data hiding process and is easily detected by a detection tool in the related technology is solved.

The present invention discloses an optical film, a polarizing plate and a liquid crystal display device for improving contrast and viewing angle, comprising an optical layer, wherein the optical layer comprises: a matrix; and a plurality of polymer dispersions, wherein the x-axis direction becomes the length direction among mutually perpendicular x-axis, y-axis and z-axis, and the plurality of polymer dispersions are randomly arranged in the matrix along the y-axis and z-axis directions, and the plurality of polymer dispersions contain a light absorber, and in the cut surface of the optical layer as the y-z plane, the width of the polymer dispersion is less than 300nm. The present invention can improve contrast, in particular, improve front contrast and side contrast at the same time, thereby improving visibility, and does not reduce brightness characteristics, and can improve viewing angle while improving contrast.

A method for determining whether to identify an image or video. The method includes detecting a person in an image or video by determining a person image area corresponding to a boundary of the person or a facial image area corresponding to a position of the person's face. The method further includes analyzing pixel values ​​corresponding to the person or the position of the person's face based on the boundary of the person or the facial image area to generate an identification avoidance signal. The method further includes determining whether the identification avoidance signal indicates that an action was taken to prevent identification of the person. The method further includes refusing to identify the person in response to the identification avoidance signal indicating that the action was taken to prevent identification of the person.

The present invention discloses an intelligent industrial PLC control cabinet device with remote monitoring, which relates to the technical field of control cabinets, including a cabinet body, a monitoring and protection module provided on the cabinet body, the monitoring and protection module being used for remotely monitoring the humidity in the cabinet body and the safety status of the cabinet body, the monitoring and protection module comprising an eaves plate fixedly installed on the front of the cabinet body, an infrared sensor and a monitoring camera installed at the bottom of the eaves plate, a moisture-proof box penetrating and connected on both sides of the cabinet body, and a humidity sensor installed on the inner wall of the moisture-proof box away from the cabinet body. The present invention is provided with a monitoring and protection module to detect whether there is a non-staff member staying in front of the cabinet door and whether the person performs illegal actions, and to warn and expel the person when the illegal actions are performed, and the humidity sensor detects whether the desiccant bag needs to be replaced, and when it needs to be replaced, the remote output drive adjustment instruction is replaced, so as to achieve the purpose of remote monitoring and remote adjustment of the control cabinet, and improve the intelligence and management efficiency of the control cabinet.

The present disclosure proposes a graphic code generation method, device and computer-readable storage medium, which relate to the field of identification code technology. The present disclosure provides a graphic code generation method, including: obtaining a target number of iterations based on a predetermined iteration rule according to the data to be carried; generating a graphic code of the data to be carried according to a predetermined self-similar set graphic generation rule and the target number of iterations. Through such a method, the data to be carried can be converted into the number of iterative processing of the self-similar set graphic, and the graphic code of the data can be generated according to the predetermined self-similar set graphic generation rule, thereby avoiding directly identifying the information to be carried from the graphic code, and improving the security of the information carried; and even if the graphic generation rule is cracked, it is difficult to forge a graphic code carrying hazardous information, reducing security risks.

This invention provides a proactive defense method and system, comprising: determining whether the attacker is a historical attacker; for historical attackers, responding to the attacker's request using a corresponding honeypot; for non-historical attackers, forwarding attack traffic to a honeypot cluster to obtain a honeypot response; determining whether the honeypot response is within a denial domain; using the honeypot corresponding to the honeypot response not within the denial domain as the honeypot responding to the attacker's request; if multiple honeypot responses are all within the denial domain, adopting a random response strategy to confuse the attacker; recording the response message generated by the honeypot responding to the attacker and the attacker's characteristics in the log; the log also includes a mapping list; to improve the overall robustness and deception of the system.

A wearable camera posture monitoring and recognition system and method, the system includes: a head-mounted wear frame, a camera, a head-mounted micro camera, which is fixedly connected to the head-mounted wear frame and is used to obtain scene video information; a projection device, which projects onto the same scene shot by the micro camera to enhance information; by adjusting the optical axis direction of the projection device, the center position of the projection pattern is located on the optical axis of the head-mounted micro camera; a prompt module, which issues a prompt when an abnormality occurs in the system; an angle perception module, which is used to obtain the angle posture information of the head-mounted micro camera, and the angle posture information includes: viewing angle θ and elevation angle ω. This system solves the problems that the head-mounted camera is prone to fail to capture or incompletely capture the operating scene, and the head movement affects the experimental scoring results. This system adopts multi-projection area technology to achieve accurate guidance of user behavior and avoid identifying other irrelevant equipment.

A user equipment (“UE”) in a wireless communication network can generate a padded identifier by inserting a string of padding bits in a field of an identifier associated with the UE. The UE can further encrypt the padded identifier to generate a hidden padded identifier. The UE can further transmit the hidden padded identifier to a network node operating in the wireless communication network.

The present invention discloses a video analysis method, device and computer equipment, which are executed by nodes corresponding to a target area, and the method includes: obtaining data information collected by at least one camera device in the target area, the data information including identification information, time information, and video information; based on the identification information and time information, selecting a target algorithm for identifying the video information from a preset model algorithm set; performing image extraction on the video information according to a preset frequency to obtain image information of a preset number of frames; using the target algorithm to identify each frame of image information to obtain an identification result corresponding to each frame of image information; and determining whether there is abnormal information in the video information according to the identification result. In this way, the waste of network resources is avoided, the problem of insufficient computing resources is solved, and the recognition accuracy is improved.

The invention provides a vehicle window position determining method and device and electronic equipment. The method comprises the following steps: acquiring target current data of a motor; the motor is used for driving the window to move; calculating an ascending amplitude ratio and a descending amplitude ratio corresponding to the target current data; determining the number of current ripples according to the ascending amplitude ratio and the descending amplitude ratio; and according to the number of the current ripples, determining the vehicle window moving distance. On the basis of the method, small waveforms generated by current jitter can be prevented from being recognized as the current ripples, the calculation accuracy of the number of the current ripples is improved, and then the calculation accuracy of the vehicle window moving distance is improved.

This invention relates to a method for multi-factor authentication passwords. It automatically generates corresponding matching features by continuously recording the relatively fixed characteristics of a user's password input habits, and automatically invokes these matching features for verification in case of verification anomalies. Because these matching features possess strong personal characteristics and long-term stability, they significantly improve security against technical decryption, brute-force attacks, and credential stuffing attacks. Furthermore, these matching features do not require separate configuration, achieving the technical effect of improving password verification security and reliability without increasing the user's learning cost or verification methods.

The present application relates to the technical field of unmanned aerial vehicle signal identification, and discloses an unmanned aerial vehicle signal identification method, an electronic device and a computer readable storage medium, the method comprising: obtaining a target signal image obtained by detecting a target unmanned aerial vehicle, the target signal image comprising frequency distribution information of a target signal; the duty ratio of the target signal is greater than a preset duty ratio threshold; amplifying the resolution of the target signal image according to a preset amplification factor to obtain an amplified signal image; identifying a plurality of edge contours of a target signal in the amplified signal image to obtain a plurality of first target areas on the amplified signal image; and reducing the resolutions of the plurality of first target areas according to a preset magnification factor to obtain a plurality of second target areas so as to identify target information of the target unmanned aerial vehicle according to the plurality of second target areas. In this way, the accuracy of unmanned aerial vehicle signal identification is improved.

The invention discloses a vertical federated learning-oriented hidden backdoor attack method, device and product, and the method comprises the steps: analyzing two attack modes of an input space and a potential space, and researching the risk that an attacker embeds a backdoor into a vertical federated learning model under the condition that global data or labels are not directly intervened; the input space attack is characterized in that in a vertical federation learning model training process, part of input samples are replaced and a trigger is injected, so that a top-layer model learns association between a backdoor trigger and a target label, and the top-layer model is guided to carry out error classification on the samples with the trigger in a reasoning stage; according to the potential space attack, an attacker directly acts on a feature embedding space of a local model of the attacker in the training process of the vertical federated learning model, and an embedding vector is adjusted by utilizing an optimization strategy so as to generate a specific backdoor response in a top layer model. According to the method, a solid foundation is laid for design and optimization of a defense mechanism, and security improvement of the VFL technology is promoted.

Disclosed are a display device capable of operating in a normal mode or a standby mode including a low afterimage mode, and an electronic apparatus including the display device, the display device including: a display panel including pixels; a gate driver providing a gate signal to the pixel; an emission driver providing emission signals defining a non-emission period and an emission period to the pixels; a data driver supplying a data voltage to the pixels; and a controller controlling the gate driver, the emission driver, and the data driver. The number of pulses of the gate signal in the non-emission period in the low afterimage mode is greater than the number of pulses of the gate signal in the non-emission period in the normal mode. The ratio of the non-transmission period to the frame period in the low afterimage mode is smaller than the ratio of the non-transmission period to the frame period in the normal mode.

The invention belongs to the technical field of industrial defect detection, and particularly relates to a fuzzy labeling defect detection method based on brightness adaptation enhancement and content perception. The method comprises the following steps: firstly, acquiring a fuzzy annotation data set, and performing data enhancement by adopting a brightness adaptive data enhancement mode to obtain an enhanced data set; then, a defect detection model composed of a deformable attention-based feature extraction network, a content-aware efficient aggregation feature fusion network and a detection head is constructed, and the deformable attention-based feature extraction network comprises a backbone network of a YOLOv8 model and a deformable attention module; and finally, training a defect detection model by using the enhanced data set, and using the trained defect detection model for defect detection. The brightness adaptation data enhancement fully considers the brightness difference between the source image and the target image, the two images are allowed to be mutually enhanced only when the brightness difference meets the condition, the large brightness difference between the defect and the background in the enhanced image is avoided, the pasting position is selected at the common position of the defect, and the visual consistency of the defect and the target image is improved; the model focuses on the common characteristics of the defects, and the detection accuracy is improved.

The invention provides a construction method and application of conditionally replicative Ad5 / 35 chimeric oncolytic adenovirus, and belongs to the technical field of genetic engineering. The construction method comprises the following steps: carrying out enzyme digestion on a PoAd5 plasmid by endonuclease AsiSI; the method comprises the following steps: carrying out in-vitro gene synthesis on a chimeric Ad5 / 35-Hexon (HVR1 + 5) gene segment, carrying out homologous recombination on the chimeric Ad5 / 35-Hexon (HVR1 + 5) gene segment and linear PoAd5 co-transfected BJ5183 to obtain PoAd5 / 35-H, carrying out ClaI enzyme digestion, carrying out in-vitro gene synthesis on Ad5 / 35-Fiber, and carrying out homologous recombination on the Ad5 / 35-Fiber and linear PoAd5 / 35-H co-transfected BJ5183 to obtain a final plasmid oAd5 / 35-HF; and carrying out PacI enzyme digestion, purifying, and transfecting an HEK293 cell to obtain the conditionally replicative Ad5 / 35 chimeric oncolytic adenovirus. The invention provides an innovative adenovirus vector construction scheme for enhancing the infection ability and the treatment effect of viruses.