221 results about "Information recovery" patented technology

The invention relates to the technical field of crop yield analysis, in particular to a crop yield prediction method based on a time sequence remote sensing image, and the method comprises the steps: obtaining an optical remote sensing image and a synthetic aperture radar image in a crop growth period, and constructing a time sequence image through complementary information fusion and under-cloud information recovery; the problems of cloud interference and data missing are solved, a multi-scale time regulation and control convolution module is used for processing a time sequence image, multi-scale time sequence features are extracted, feature fusion is carried out in combination with attention difference jump connection, and a rice distribution map is obtained; determining a rice planting area based on the rice distribution diagram, selecting an optimal assimilation time period in the rice planting area, and assimilating the leaf area index subjected to remote sensing inversion and a crop growth model simulation result to generate a simulated yield after assimilation; based on the multi-scale time sequence characteristics, a parameter dynamic response matrix related to crop growth model parameters is established, and residual error correction is performed on assimilated simulation yield, so that the rice yield prediction precision is improved.

The application discloses a ciphertext decryption method and related equipment applied to ciphertext encrypted according to an RSA algorithm, and the method comprises the following steps: acquiring a large number in ciphertext and a public key of the ciphertext; selecting a number smaller than the large number as a base of a discrete logarithm problem, selecting 1 as a modulus power operation result corresponding to the base, and converting the base and the modulus power operation result into an initial quantum state; inputting the initial quantum state into a quantum computing module for solving the discrete logarithm problem to obtain a first target quantum state in which a solution result of the discrete logarithm problem is stored; extracting the solution result from the first target quantum state, and calculating a private key of the ciphertext based on the solution result; and decrypting the ciphertext based on the private key to obtain plaintext of the ciphertext. Through the technical scheme, the private key can be recovered according to the disclosed information in the case that the private key is not disclosed, and then the ciphertext is decrypted, so that the related technical blank is filled.

The invention provides a hot upgrade method for a virtual machine monitor (VMM), which comprises the following steps of: pausing the operation of a virtual machine, storing state information of an original VMM, and reserving a kernel-based virtual machine KVM extension page table and a memory management structure of the original VMM; reserving a page global directory and a virtual memory area VMA corresponding to a virtual machine RAM area according to the memory management structure, and refreshing a process address space described by the memory management structure into a new VMM execution program so as to complete switching of the original VMM into the new VMM; and executing the new VMM, recovering the state information to the new VMM, and inheriting the KVM extension page table by the new VMM to recover the operation of the virtual machine. The invention further provides computer equipment, a computer readable medium and a computer program product.

The invention discloses a screen shooting traceability method, device and equipment and a readable storage medium, which are applied to the field of computer software, and comprise the following steps: encoding watermark information to obtain a watermark information sequence; embedding the watermark information sequence into the image through an R channel, a G channel and a B channel of RGB (Red, Green, Blue) to obtain an image with a watermark; and acquiring the shot image with the watermark image, and tracing to obtain watermark information based on the shot image. According to the method, the watermark is generated by using the RGB channel of the single pixel image, so that the visual concealment of the watermark image is improved, the difficulty in perceiving of human eye recognition is ensured, and the visual quality of a user is not influenced; the watermark embedding position is not influenced by an original image carrier, and watermark information can be hidden in any area of the image; and the watermark information recovery success rate is high.

The invention provides an RAID (redundant array of independent disks) data processing method and device, a chip, electronic equipment, a storage medium and a computer program product, and is applied to RAID, the method comprises the following steps: detecting that at most three storage devices fail, determining at most three corresponding to-be-recovered areas in a stripe, and storing the to-be-recovered areas in the stripe; the to-be-recovered area is a data area, a verification area, a first hot standby area and / or a second hot standby area; determining a target area based on at most three areas to be recovered, wherein the target area is a data area, a verification area, a first hot standby area and / or a second hot standby area except the areas to be recovered; and target information in the target area is read, and the data information and / or the first verification information of the to-be-recovered area are / is recovered based on the target information.

The invention relates to a data recovery method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: receiving a data reading command, and determining protection information of target data corresponding to the data reading command; the APP domain information in the protection information comprises bad sector mark BST information corresponding to a sector where the target data is located; under the condition that the BST information is damaged, verification information corresponding to the APP domain information is determined in the APP domain stripe; verifying the APP domain information according to the verification information to obtain recovered APP domain information; the recovered APP domain information contains the recovered BST information. By adopting the method, the data recovery efficiency can be improved.

The embodiment of the invention provides a low-illumination image enhancement method and system based on frequency decomposition and multi-scale fusion, and the method comprises the steps: obtaining a to-be-processed image, and decomposing the to-be-processed image into a low-frequency component feature map and a high-frequency component feature map through employing an iterative mean filter; a low-frequency tensor is generated based on the low-frequency component feature map, and a high-frequency tensor is generated based on the high-frequency component feature map. And fusing the high-frequency tensor and the low-frequency tensor to generate an enhanced feature map. According to the method, iterative mean filtering can be applied to separate frequency bands, and an image to be processed is decomposed into a high-frequency component and a low-frequency component. More accurate image enhancement is realized through different sub-networks, that is, a high-frequency enhancement network focuses on detail reconstruction and noise suppression, and a low-frequency enhancement network is responsible for recovery and transformation of illumination and color information, so that the image enhancement quality can be improved, and the problem of poor image enhancement effect is solved.

The invention discloses a covert communication system based on a generative diffusion model, and belongs to the technical field of covert communication. In order to solve the problems of insufficient concealment and poor anti-noise performance in the prior art, hidden transmission and reliable recovery of information are realized by constructing a diffusion generation and classification discrimination module. The sending end carries out noise addition and shaping on the original bit waveform by using a forward diffusion process to form a noise-like hidden signal; and a receiving end recovers a signal structure through a reverse denoising process, and accurately judges bit information through a classifier. According to the method, a Gaussian approximation hidden waveform library is constructed by adopting a signal pair training model which is consistent in statistics but distinguishable in structure, and random sampling mapping and boundary smooth splicing are combined, so that transmission signals are difficult to distinguish from noise in a frequency domain and a feature space; therefore, the avoidance capability, the anti-interference robustness and the information recovery accuracy under the low signal-to-noise ratio of the detection means are remarkably improved.

The invention provides a gradient matching attack method of a Vision Transform (ViT) model aiming at noise disturbance, and relates to a privacy protection problem in a federated learning scene. The method specifically comprises the steps of providing a gradient denoising method based on a diffusion model, recovering disturbed gradient data through reverse noise prediction, and designing a gradient diffusion denoising network for attention perception to solve the problem of feature distortion caused by traditional Gaussian noise. On the basis, a gradient matching attack method for ViT is provided, and high-fidelity semantic information recovery of noise-added gradient is realized by analyzing gradient distribution characteristics of a ViT model and combining a position coding gradient extraction and optimization reconstruction technology. The method disclosed by the invention reveals the vulnerability of the ViT model with noise disturbance when facing gradient leakage attacks, provides a confrontation view angle and thinking enlightenment for constructing a ViT privacy protection mechanism, and has important application value in privacy sensitive fields such as medical image analysis and financial risk control.

The invention relates to a recoverable visual encryption method for a human body privacy area in an image collected by an unmanned aerial vehicle. The method comprises the following steps: constructing a joint deep learning model integrating a pre-training target detection module, a self-adaptive visual encryption module and an enhanced visual decryption module; in the training stage, target detection module parameters are frozen, and an encryption and decryption module is optimized end to end through combined loss formed by a composite decryption loss function and an encryption strength loss function; during application, the target detection module accurately locates a human body sensitive area, the encryption module applies size-adaptive and strength-learnable pixelated transformation to generate a natural encryption image, and the decryption module realizes high-fidelity original information recovery through an enhanced U-Net network under an authorization condition. Compared with an existing traditional image encryption or irreversible desensitization technology, the method has the advantages that seamless integration with a mainstream target detection process is achieved, the integrity and restorability of information are guaranteed while high visual concealment is achieved, and the method has the advantages of being intelligent, high in efficiency and high in practicability.

The invention provides a database log analysis and recovery method and device, equipment, a medium and a program product, and relates to the field of data processing. Periodically generating a snapshot file of cache record data involved in a database log analysis process, and recording a snapshot identifier corresponding to the snapshot file; updating version information of a data dictionary, and binding the snapshot identifier with the version information of the data dictionary; when database log analysis is interrupted, matching corresponding target version information from the data dictionary according to a target snapshot identifier; recovering the state of the cache record data based on the target version information, and determining the initial position of database log analysis; according to the method, the snapshot file of the cache record data is periodically generated, and the snapshot identifier and the data dictionary version information are bound, so that the cache data state and the analysis starting position are quickly recovered based on the latest snapshot after the database log analysis is interrupted, and the fault tolerance and the recovery efficiency of log analysis are improved.

The invention provides a communication method and a communication device, and the method comprises the steps that a second device obtains first indication information from a first device, the first indication information is used for determining a time unit in which reset state information of a first artificial intelligence AI model takes effect, and the second device can determine according to the first indication information, and a time unit for enabling reset state information of the first artificial intelligence (AI) model. According to the scheme of the embodiment of the invention, the robustness of the recovery performance of the channel information can be improved.

The invention belongs to the technical field of wireless communication, and particularly relates to a communication sensing integrated system based on non-orthogonal AFDM (Alternating Frequency Division Multiplexing). According to the system, a bandwidth compression factor is introduced into an AFDM framework to construct a non-orthogonal waveform, and controllable overlapping between chirp subcarriers is realized, so that the spectrum utilization rate is improved, and the robustness of the system under a high-speed dynamic channel is enhanced. And a receiving end realizes reliable information recovery through maximum likelihood detection, and processes echo signals in combination with a two-dimensional parameter estimation algorithm so as to realize high-precision sensing of the target distance and speed. The system has good anti-Doppler capability and perception precision performance, and is suitable for communication perception fusion application in a high-speed mobile scene.

The invention discloses a monocular vision-based structure displacement measurement method under a high-temperature working condition, and particularly relates to the field of monocular vision-based image analysis from a bit image to a non-bit image, and the method comprises the steps: extracting a local gray level feature set and carrying out the statistics of gray level distribution parameters based on a continuous frame gray level image sequence collected by a monocular vision system; judging and screening preliminary connected regions, establishing a region degradation probability graph, and constructing a standard Markov random domain graph structure; based on a standard Markov random domain graph structure, a gray gradient feature set is extracted, a local gradient disturbance vector field is established, and a disturbance potential energy graph is generated. By constructing a variation Markov random domain model based on local gray features and mutual information entropy adjustment and combining dynamic degradation characteristic extraction and reference point time sequence trajectory analysis, structural information recovery and displacement measurement of a local degradation region under a high-temperature working condition are realized. And the problems of image connectivity loss and structure tracking failure caused by optical window degradation are solved.

The embodiment of the invention provides a software content layout data processing method and device, and the method comprises the steps: receiving template data, annotation data and configuration data of a preset software template, carrying out the structural analysis of the template data according to a template analysis engine, determining a structural analysis result, initializing the configuration data according to a rule engine, and carrying out the structural analysis of the configuration data. And determining a rule engine instance, based on the structure analysis result and the rule engine instance, performing standardized preprocessing on the template data through a template preprocessing engine, determining a standardized template structure, and replacing the template content of the standardized template structure according to the annotation data. According to the method and the device for replacing the small red book template, the template is replaced, the labeling information recovery operation, the spacing deviation recovery operation, the exceeding detection operation and the layout adjustment operation are sequentially executed on the basis of the replaced template, and a final template structure is obtained for a user to use, so that the small red book template typesetting efficiency and quality can be improved.

The present invention relates to the technical field of crop yield analysis, and specifically to a crop yield prediction method based on time-series remote sensing images. In the present invention, optical remote sensing images and synthetic aperture radar images during the crop growth period are acquired, and time-series images are constructed through complementary information fusion and cloud-underground information recovery. Cloud interference and data missing problems are addressed, and a multi-scale time-regulated convolution module is used to process the time-series images, extract multi-scale time-series features, and perform feature fusion in combination with attention differential jump connections to obtain a rice distribution map. Rice-planting areas are determined based on the rice distribution map, and an optimal assimilation period is selected within the rice-planting areas. A leaf area index obtained by remote sensing inversion is assimilated with crop growth model simulation results to generate an assimilated simulated yield. Based on the multi-scale time-series features, a parameter dynamic response matrix related to crop growth model parameters is established, and residual correction is performed on the assimilated simulated yield, thereby improving the accuracy of rice yield prediction.

The invention discloses a depth guidance image defogging method and system for deep ground medical rescue, and aims to improve the visibility of medical rescue monitoring images and the accuracy and real-time performance of structural information recovery in deep ground environments such as mines. By introducing a scale collaborative attention module, collaborative learning of multi-scale features is realized, scale confusion is relieved, and the cross-scale feature collaboration capability is enhanced; and meanwhile, an error perception guide module is adopted to fuse local feature difference and global dependence, and mutual promotion optimization is performed on defogging and depth estimation tasks, so that more accurate image restoration is realized in a region with a complicated structure or non-uniform fog distribution. According to the method, close collaborative optimization and performance improvement between image defogging and depth estimation tasks can be realized, and the problems of scale confusion and limited scale collaborative capability in multi-scale feature learning can be solved to a certain extent.

The invention provides a deep and large fracture depicting method based on low-frequency electromagnetic information recovery enhancement, and the method comprises the steps: S1, collecting electromagnetic data, and carrying out the preprocessing of the electromagnetic data, and obtaining the preprocessed electromagnetic data; s2, obtaining frequency domain apparent resistivity and phase according to the preprocessed electromagnetic data; s3, establishing a shallow stratum electrical model; s4, acquiring a depth domain apparent resistivity profile according to the shallow stratum electrical model; and S5, depicting deep and large fracture distribution based on the depth domain apparent resistivity profile. According to the invention, enhancement of low-frequency electromagnetic signals is realized, the inversion precision of electromagnetic data is improved, low-frequency geological information is effectively recovered, and deep and large fractures can be effectively described.

The present disclosure provides an encryption and decryption system and method. The encryption and decryption system includes a transmitting device and a receiving device. The transmitting device is configured to store a plurality of original images. The receiving device is connected to the transmitting device and configured to store a corresponding table. The transmitting device generates an encrypted string, selects a representative transformed image from the plurality of transformed images according to the encrypted string, transmits the representative transformed image to the receiving device, and does not transmit the encrypted string to the receiving device. The receiving device identifies a first original image number and a second original image number from the representative transformed image, and looks up the corresponding table according to the first original image number and the second original image number to generate the encrypted string. Thus, various network attacks can be prevented, resource and time consumption can be greatly reduced, the problem of excessive distortion or low capacity of embedded data can be solved, and the information recovery capability can be greatly improved.

The invention discloses an image processing method, an image processing device and image processing equipment based on palette prediction, and aims to solve the problem of inconsistent coding and decoding caused by lack of prediction information construction in a decoding process of a palette prediction mode if the palette prediction mode is adopted during loop filtering coding based on a low-complexity neural network. Meanwhile, compression performance can be improved to a certain extent, the embodiment of the invention provides a solution, existing coding information or information which can be obtained by a coding end and a decoding end is used as prediction information of loop filtering of the low-complexity neural network, the prediction information is input into a loop filtering model of the low-complexity neural network, and the compression performance of the low-complexity neural network is improved. According to the method, for a block with the optimal prediction mode being a palette prediction mode, reconstruction information output after the loop filtering model of the low-complexity neural network is processed is recovered into reconstruction information stored before the loop filtering model of the low-complexity neural network is processed, so that the coding and decoding consistency can also be kept, or for a block with the optimal prediction mode being a palette prediction mode, reconstruction information output after the loop filtering model of the low-complexity neural network is processed is recovered into reconstruction information stored before the loop filtering model of the low-complexity neural network is processed.

The present application relates to a kind of information recovery methods based on scattering system, belong to spectral data processing technical field.The method is: the scattering characteristic of scattering system is calculated;Using the scattering characteristic calculated, establish scattering signal self-excitation amplification mechanism;On the scattering signal self-excitation amplification mechanism, incident light field time domain, space domain, frequency domain coding and trend decoding, wave analysis, to nearly completely recover scattering information;Using negative correlation statistical operation obtains the accurate scattering information of high noise scattering system.The present application is amplified by the scattering signal of special self-excitation method, based on light field composite coding and scattering information trend analysis, accurately judges input field information;By introducing negative correlation operation, can nearly completely recover incident field information, realize the nearly complete evaluation of the scattering characteristic of extremely high noise system.The present application promotes the progress of imaging technology not limited by the thickness of scattering medium, further promotes the development of realizing human clinical high-resolution optical reflection, transmission imaging.

The invention relates to the technical field of artificial intelligence and big data, and discloses a vector compression reconstruction method for long text semantic retrieval, which comprises the following steps: firstly, segmenting a long text T into n text segments S1, S2,..., Sn according to semantic similarity or a fixed length; secondly, for each text segment Si, generating a local semantic vector li by using a BERT pre-trained language model, and converting the input text segment Si into a high-dimensional vector by the BERT model; then global vector generation is carried out, specifically, weighted average is carried out on the local vectors li, l2,..., ln of all the segments through a weighted average method, and a global semantic vector g is generated; carrying out explicit compression and key information storage; performing staged hybrid semantic retrieval; cross-segment semantic reconstruction and reasoning are carried out, and context information recovery is carried out; performing dynamic semantic reconstruction; and generating answers based on the reconstructed context. According to the method, deeper reasoning can be carried out, and more accurate and more comprehensive answers are generated.

The invention discloses a target extraction method and device for linear cultural heritage ruins and relics. The method comprises the following steps: acquiring a remote sensing image of a linear cultural heritage; inputting the remote sensing image into a network feature extractor for multi-level feature extraction to obtain shallow layer features, middle layer features and high layer features; performing target semantic enhancement on the deep features to obtain enhanced deep features; carrying out attention and fusion operation on the shallow-layer features and the middle-layer features to obtain shallow-layer fusion features and middle-layer fusion features; performing gating attention fusion and information recovery operation on the enhanced deep-layer features, the shallow-layer fusion features and the middle-layer fusion features to obtain features after information recovery; performing linear feature reconstruction on the features after information recovery to obtain reconstructed features; and inputting the reconstruction features into a segmentation head and an auxiliary divider to obtain a prediction result. The method can achieve the automatic extraction and precise recognition of the large-scale linear cultural heritage.

The invention provides an OCTA retinal vessel segmentation method for improving U-Net based on adjacent feature extraction, and belongs to the field of medical image processing. According to the method, on the basis of a U-Net network, feature maps of adjacent layers are combined through a Proximal Feature Merge (PFM) module, and the capability of segmenting small blood vessels is remarkably improved; meanwhile, a shallow feature complementation module (SFC) is introduced, feature maps of different levels of an encoder are combined at the deepest level, and connectivity of segmented blood vessels is effectively guaranteed through a series of information recovery; in order to adapt to small blood vessels and refined edge information, a BottleUnext module is further added in the method, the resolution of the feature map is gradually amplified, then complex features are extracted, and finally the resolution of the feature map is recovered. Experiments show that compared with an existing method, the method shows more advanced performance in an OCTA retinal blood vessel task, and accurate segmentation of the retinal blood vessel is achieved.

The present application provides a power control device that can suppress the power consumption reduction effect obtained by leveling execution from being weakened by suppressing the power consumption amount after leveling execution. The power control device includes a communication unit and a control unit. The control unit stores information of a leveling instruction and information of a recovery mitigation request. The information of the leveling instruction includes information of an execution time and information of a first allowable average power in the execution time. The information of the recovery mitigation request includes information of a recovery period and information of a second allowable average power in the recovery period. The control unit controls the driving of a power load device in such a manner that the average consumption power of a facility in the execution time becomes lower than the first allowable average power, and controls the driving of the power load device in such a manner that the average consumption power of the facility in the recovery period becomes lower than the second allowable average power. The second allowable average power is greater than the first allowable average power.

This invention provides a gaming machine that partially unifies the backup and recovery process, which restores predetermined information to its pre-game state, with the backup process, which backs up the predetermined information, thereby reducing the pressure on the program area capacity of the main ROM. [Solution] In the game start state control process of the main process, a backup of various information is acquired, and further, in the game end state control process of the main process, a process is provided to restore the backed-up various information according to predetermined conditions. In this process, when backing up and when restoring the various information, the values ​​of the registers that store the addresses of the respective data storage areas are swapped, thereby making some of the programs common.

This invention provides a method for constructing a power distribution system fault recovery agent based on large-scale and small-scale model collaboration. The method includes: retrieving large-scale model prompts and context from a pre-built knowledge base based on received fault information recovery statements; decomposing the fault information recovery statements into several sub-tasks according to a task decomposition prompt template, and calling the corresponding small model to execute each sub-task; generating a first recovery strategy based on the large-scale model prompts, the large-scale model context, and the fault information recovery statements; generating a second recovery strategy based on the output results of all small models; and using the first and second recovery strategies as the output fault recovery strategies to perform fault recovery on the power distribution system. This invention, by employing a large-scale and small-scale model collaboration method, effectively leverages the excellent text semantic understanding and extraction capabilities of large language models, overcoming the difficulty of extracting and utilizing the large amount of prior knowledge in text form from power systems for intelligent agents.

The application provides a heat-aware storage engine performance optimization method, which comprises the following steps: determining a target database, initializing a maximum heap in the memory of the target database, and maintaining the file heat of the system; reading file heat information from the log of the target database, and recovering the file heat identification mechanism based on the maximum heap; writing the file heat information into a Memtable of an LSM-tree memory component by a storage engine, and making the data of the Memtable fall to the disk and generate a CuckooTable file; establishing a Bloom filter for the CuckooTable file on an NVM; recording the corresponding relationship between the Bloom filter and the file in an index queue; and updating the index queue when the number of files in the LSM-tree reaches a preset threshold. The method provided by the application can be used to optimize the performance of a storage engine designed with a LSM-tree structure.

The invention discloses a color steel tile illegal building segmentation detection and geographic information recovery method and system based on deep learning, and relates to the technical field of image processing, and the method comprises the steps: carrying out the preprocessing of collected remote sensing image data, and carrying out the production and amplification of a data set based on the preprocessed data; based on deep learning, taking the data set as input, and constructing an illegal building and illegal construction identification model; on the basis of the trained illegal building and illegal construction identification model, inputting newly collected data into the identification model, and outputting preliminary illegal sub-pictures; and splicing the preliminary violation sub-pictures in a large range, introducing the position of the electric power facility to carry out nested fine identification, and finally obtaining the spatial distribution condition of the violation building and the construction site. According to the method, the deep learning model is combined with a nesting processing method, global features and local detail features in remote sensing images can be fully extracted and integrated, and the detection accuracy and robustness of illegal buildings and construction areas in complex scenes are remarkably improved.

This invention provides a gaming machine that partially unifies the backup and recovery process, which restores predetermined information to its pre-game state, with the backup process, which backs up the predetermined information, thereby reducing the pressure on the program area capacity of the main ROM. [Solution] In the game start state control process of the main process, a backup of various information is acquired, and further, in the game end state control process of the main process, a process is provided to restore the backed-up various information according to predetermined conditions. In this process, when backing up and when restoring the various information, the values ​​of the registers that store the addresses of the respective data storage areas are swapped, thereby making some of the programs common.