153 results about "Restoration method" patented technology

The invention provides a chemical restoration method for treating heavy metal-polluted terrain soil by ferromagnetic artificial nucleuses. In a ferromagnetic artificial nucleus soil restoration method, the ferromagnetic artificial nucleuses are applied to heavy metal-polluted soil; soil above a heavy metal pollution depth is overturned by cultivation equipment to uniformly mix with the ferromagnetic artificial nucleuses; and after heavy metal can be dispersed from the soil to the artificial nucleuses by a period of time, the soil containing the artificial nucleuses is overturned by using the cultivation equipment to increase the change of the artificial nucleuses contacting with other soil. After the soil overturning procedure is repeated by multiple times, the cultivation equipment provided with magnets can be used for separating the ferromagnetic artificial nucleuses, absorbed with the heavy metal, from the polluted soil; and the content of the heavy metal of the polluted soil is reduced due to shifting-out of the ferromagnetic artificial nucleuses, so that the purpose of soil restoration is gradually achieved.

The invention discloses an ancient fresco restoration method based on progressive reconstruction and damage perception self-adaption, and relates to the technical field of computer vision and image processing, a damaged fresco image is input into a coarse restoration network for initial restoration, in the initial restoration process, a discriminator and the coarse restoration network are adopted for adversarial training, and a damaged fresco image is obtained; generating an initial restoration result of the mural image; inputting the initial repair result and the mask image into a mask-guided local information extraction network to obtain a local optimization result; and inputting the local optimization result into a global information extraction network to obtain an overall restoration result of the mural image. The problem that an existing network is low in efficiency in the aspect of capturing local details and global styles is solved. The method has good applicability to damaged wall paintings; the problem of fuzzy texture in the repairing result is effectively solved; local features are adaptively extracted and fused according to the damage degree of the mural, and the multi-stage residual information distillation module further refines details of the mural on different scales.

The invention belongs to the technical field of computer vision three-dimensional scene repair, and provides an automatic driving three-dimensional scene repair method based on color point cloud prior guidance, which comprises the following steps: acquiring multi-source heterogeneous data; constructing an incomplete semantic two-dimensional Gaussian field according to the multi-source heterogeneous data, and generating an incomplete image sequence, an incomplete depth image sequence and an opacity image sequence; obtaining a color point cloud based on the instance segmentation image, the opacity image, the incomplete image and the incomplete depth image of the reference image; generating a texture pseudo view angle sequence based on the color point cloud; generating a repaired image sequence by taking the texture pseudo view angle sequence as a condition signal of the fine-tuning video diffusion model; generating a repair depth sequence based on the color point cloud; calculating a repair Gaussian loss function based on the repair image sequence and the repair depth sequence, and performing iterative repair optimization on the incomplete semantic two-dimensional Gaussian field to obtain a complete repair two-dimensional Gaussian field; the invention further discloses a computer device. And texture-geometry collaborative automatic driving scene three-dimensional repair is realized.

The invention relates to the technical field of image processing and cultural relic protection, in particular to a cultural relic image virtual restoration method based on texture reconstruction and color correction, and the method comprises the following steps: S1, obtaining a digital image of the surface of a to-be-restored cultural relic, and carrying out the denoising and brightness equalization processing of the digital image; s2, identifying and segmenting a damaged area in the image; s3, selecting an optimal sample block which is most matched with the structure of the region to be filled; s4, performing adaptive affine transformation on the optimal sample block to generate a reconstructed texture block; s5, carrying out linear transformation to obtain a repaired texture block after color correction; and S6, seamlessly embedding the repaired texture block after color correction into the damaged area. According to the method, the texture direction alignment and the color distribution correction are combined, so that the consistency of the damaged area and the surrounding image in structure and color is realized, and the naturalness and integrity of cultural relic image restoration are remarkably improved.

The invention discloses a chapter-level Chinese ancient book image restoration method and related equipment, and belongs to the field of ancient book restoration. The method comprises the following steps: acquiring ancient book images, and screening out intact ancient book images and damaged ancient book images; for an intact ancient book image, simulating damage in a random mask mode, and constructing a training data pair; for the damaged ancient book image, marking the position of the incomplete character, and determining the specific content of the incomplete character; constructing a repair model based on the diffusion model, and training the repair model; and using the trained model to gradually realize the restoration of the chapter-level ancient book image in the form of an overlapped sliding window in an autoregression mode. According to the method, on the basis of the damaged positions and the damaged text content of the ancient books marked by human experts, the diffusion model technology is adopted, an autoregressive restoration method is combined, automatic restoration of the chapter-level damaged ancient book image is achieved, and the overall consistency of the font style and the background is effectively kept in the restoration process.

The invention discloses a historical document restoration method and system based on implicit interpolation network enhancement. The method comprises the following steps: acquiring a damaged historical document image, a position mask image for identifying a to-be-restored area and a content guide image for guiding the semantic meaning of restored content; constructing a historical document repair model based on a de-noising diffusion probability model; training the historical document repair model by using a training data set containing damaged image and intact image pairs; and inputting the damaged historical document image to be repaired, the position mask image and the content guide image into the historical document repair model, and outputting the repaired historical document image. According to the method, the accuracy of the character content in the restoration area and the naturalness of the visual boundary are remarkably improved, and high-fidelity digital restoration of complex degraded literatures such as ancient books and inscription rubbings is realized.

The invention discloses a lightweight mural virtual restoration method based on an inactive generative model, and belongs to the technical field of digital image processing and computer vision. The objective of the invention is to solve the technical problem of semantic and texture recovery imbalance of an existing deep learning repair model in face of cultural heritage such as murals. A damaged image and a mask are stacked into a multi-channel tensor to be input into a pre-trained AFMNet model, the model adopts an encoder-bottleneck-decoder architecture, and an encoder uses a multi-domain partial convolution module without an activation function to synchronously extract and fuse local texture and frequency domain global structure information and synchronously update the mask; the bottleneck portion models the lowest resolution features and masks thereof through a lightweight multi-head attention module to capture remote dependencies, and a decoder upsamples in conjunction with the features of the jump connection transfer to reconstruct image details. The method is mainly used for carrying out efficient and high-fidelity digital virtual restoration on damaged visual cultural heritage such as ancient murals.

The invention discloses an urban shallow lake ecological protection and restoration method and system integrated with intelligent management and control, and relates to the technical field of water environment ecological management and intelligent water affairs, and the method comprises the steps: constructing a three-dimensional monitoring network to synchronously collect water quality, image and meteorological data, and carrying out the fusion to generate a multi-modal data set; a deep learning model is utilized to realize pollution source tracing, water quality prediction and algae bloom early warning in parallel; based on the prediction result, outputting a multi-facility cooperative regulation strategy through a reinforcement learning agent; and converting the strategy into a hierarchical instruction to drive an execution unit, and feeding back the treated environment state to the model and the intelligent agent to form closed-loop optimization. According to the invention, whole-course intelligent management and control from monitoring to execution are realized, systematicness, accuracy and perspectiveness of lake treatment are effectively improved, and water environment risk response capability and ecological restoration effect are significantly enhanced.

The invention discloses a goaf ecological restoration method and system based on artificial intelligence, and the method comprises the steps: obtaining multi-source remote sensing data and geological survey data of a goaf, and generating a three-dimensional geological damage model of the goaf through a space-time fusion technology; performing multi-scale feature extraction on the three-dimensional geological damage model by using a deep convolutional neural network to obtain a multi-dimensional ecological feature data set, identifying an ecologically fragile region and an instability risk region, and outputting an ecological risk level map; performing parallel processing on the multi-dimensional ecological characteristic data set to generate an ecological assessment report containing health degree scores of each ecological subsystem of the goaf; and based on the ecological risk grade map and the ecological assessment report, a multi-objective optimization algorithm is adopted to generate a vegetation-soil / rock mass-water body collaborative restoration strategy. By means of the goaf ecological restoration method and device, accurate assessment and collaborative strategy generation of goaf ecological restoration can be achieved, and scientificity, efficiency and overall ecological benefits of restoration engineering are improved.

The invention discloses a time sequence reconstruction and machine learning coupled chlorophyll monitoring data breakpoint restoration method, and belongs to the technical field of water quality monitoring. The invention discloses a chlorophyll monitoring data breakpoint restoration method based on coupling of time sequence reconstruction and machine learning, and the method comprises the following steps: S1, collecting water quality monitoring data, and cleaning the monitoring data to obtain preprocessed data; s2, performing time sequence reconstruction on the preprocessed data to obtain a weekly average 1 data set; s3, respectively constructing a radial basis function neural network model and a back propagation neural network model by taking the chlorophyll concentration as a response variable and the conventional water quality parameter as a predictive variable; s4, performing performance evaluation on each model by taking a root mean square error, an average absolute percentage error, goodness of fit and relative error distribution statistics as evaluation indexes, and screening out an optimal model; and S5, applying the conventional water quality parameters in the breakpoint interval of the chlorophyll monitoring data in the water body to the optimal model, and outputting the restored chlorophyll concentration value to complete the dynamic restoration of the breakpoint.

The invention relates to a relics restoration method based on a meta-universe and a digital twinborn technology, and aims to solve the problems of relics disappearance and historical memory deficiency in urban construction, and utilizes the meta-universe and the digital twinborn technology to build a relics 3D model on a meta-universe platform to realize scene restoration. A virtual scene is constructed through software such as 3DMAX and Unity 3D and related technologies, and the characteristics of identity, social contact, immersion and the like are achieved; the method has obvious advantages, the cost can be reduced, the efficiency can be increased, the real scene can be stably simulated, and multi-place policy support can be obtained. The market potential is large, and the method faces college teachers and students, culture enthusiasts and other groups. Popularization strategies such as social media propaganda and SEO are adopted, and the product has unique advantages and innovation and is flexible in pricing; in addition, the method has both campus and social public welfare, provides an innovative scheme for relics recovery, and is of great significance in the fields of cultural inheritance, education and the like.

The invention relates to a cultural relic virtual restoration method and device based on a digital twinning technology, equipment and a medium. The method comprises the following steps: acquiring original data of overseas lost cultural relics; performing standardized preprocessing on the original data to obtain a cultural relic data packet; performing three-dimensional geometric reconstruction based on the cultural relic data packet to obtain a cultural relic three-dimensional digital model; identifying diseases appearing in the cultural relic three-dimensional digital model through an image segmentation model to obtain a cultural relic disease list; based on the cultural relic disease list, predicting the risk of the structural stability of the cultural relic three-dimensional digital model through mechanical simulation to obtain a cultural relic risk prediction map; and based on the cultural relic disease list and the cultural relic risk prediction map, parallel generation of restoration strategies with different emphasis points is carried out, and a virtual restoration scheme is obtained. By adopting the method, the initial state of the cultural relic can be reproduced in the virtual environment, the restoration effect can be reviewed, and the potential risk can be accurately predicted.

The invention provides a mining area geology restoration method. The mining area geology restoration method comprises the steps that environmental parameters and reaction state data of a to-be-restored mining area are acquired through a sensing network; based on the environmental parameters and the reaction state data, digital twinborn bodies are constructed and run, and the digital twinborn bodies are used for simulating the migration of carbon dioxide in the to-be-restored mining area and the reaction process of the carbon dioxide and minerals; generating an injection strategy for controlling a carbon sequestration reaction process based on a simulation result of the digital twin; according to the injection strategy, injection equipment is controlled to inject a reaction medium into the to-be-repaired mining area; and performing monitoring and fault prediction on the operation state of the injection equipment, and generating a maintenance instruction. According to the invention, intelligence, precision, high efficiency and multi-target collaboration of the geological restoration process of the mining area are realized.

The invention discloses a test and output restoration method for an instruction-guided image editing model based on a metamorphic test technology, and the method comprises the steps: collecting an original input image and an editing instruction as an original test case, collecting an output image of the original test case, and comparing the input image with the output image to obtain an editing region of the original test case; converting the input image according to the metamorphic relation to generate a candidate image set, selecting an equivalent derivative test image, and forming a new derivative test case together with an original editing instruction; collecting output images of all the derivative test cases, comparing the input images with the output images to obtain editing areas of the derivative test cases, and judging whether the editing areas of all the derivative test cases are consistent with the editing areas of the original test cases or not; carrying out cross validation on all derivative test cases and the output of the original test case, selecting the output of the optimal test case, and mapping the output of the optimal test case to the original test case to serve as the restored original test output; and summarizing a test result and outputting a repair result.

The invention provides a mine operation repairing method based on an unmanned aerial vehicle and a related device, and relates to the technical field of mine repairing. Based on factors such as a topographic relief factor, a wind field turbulence intensity factor, an unmanned aerial vehicle interference factor, a throwing angle, a wind direction angle, throwing delay and the like, firstly, an initial drop point of seed settlement is given through a physical model, and deviation caused by complex wind field turbulence, unmanned aerial vehicle interference, irregular topography and the like is corrected in combination with a machine learning algorithm; according to the method, the nonlinear and interaction problems in an actual scene are considered, a quadratic term and a small number of physical meaning interaction items are adopted for feature mapping, correction is conducted through a physical model in combination with a machine learning algorithm, and accurate prediction of the seed settlement drop point can be better achieved.

The invention provides an evaluation and repair method and system for a composite bushing umbrella skirt. The method comprises the following steps: detecting and evaluating the current aging state of the composite bushing umbrella skirt to obtain an aging grade; setting a repair decision according to the aging level; and repairing the composite sleeve umbrella skirt according to the result of the repairing decision. Through the processing of the steps, the evaluation and restoration method breaks through the limitation of detection decentralization, evaluation subjectivity and restoration manual operation in the prior art, establishes a standardized grading evaluation and decision-making mechanism, constructs a whole-process automatic restoration system, and improves the accuracy of the whole-process automatic restoration. According to the method, the aging state of the composite sleeve umbrella skirt can be automatically and accurately evaluated, the repairing process is intelligently and adaptively executed, the repairing effect is verified in a closed loop mode, and standardization, automation and precision of aging repairing of the composite sleeve umbrella skirt are achieved, so that the operation and maintenance cost and dependence on manpower are greatly reduced on the premise that the repairing quality is guaranteed, and the repairing efficiency is improved. And the repair efficiency and quality of the composite sleeve umbrella skirt are improved.

The application discloses a kind of based on U-Net model's missing audio automatic repair method, including the following contents: audio signal is handled to the sample of same length and constructs multiple audio data sets;All audio samples are handled into fixed length three parts, from left to right respectively left context part, gap part and right context part;Using short-time Fourier transform, audio context part and gap part are all converted into spectrum diagram;The encoder in deep learning model carries out feature learning to the spectrum diagram of context part, and the decoder realizes the automatic repair of gap part missing audio, and the two corresponding layers are connected by jump connection to expand network receiving range, improve network repair performance;Finally, the generated spectrum diagram is converted into audio signal using local weighted summation strategy.The application uses U-Net deep learning model and local weighted summation strategy to repair missing audio, and the repair effect is good, and the calculation cost is lower, suitable for the repair of audio missing situation in short audio.

The invention discloses a firmware backdoor detection and one-key security restoration method and system, and relates to the technical field of software detection. The method comprises the steps of obtaining an original byte sequence of a firmware upgrade package; performing segmented structure analysis and standardization on an original byte sequence of the firmware upgrade package to obtain a byte interval index of each segment and an upgrade package segment list; extracting ciphertext statistical characteristics of each segment based on the byte interval index and generating an upgrade package statistical fingerprint; comparing the statistical fingerprint of the upgrade package with a historical baseline to obtain a ciphertext anomaly score; when the ciphertext exception score exceeds a verification trigger threshold value, generating an equipment end verification task and collecting equipment end verification evidence; performing fusion judgment on the basis of the ciphertext anomaly score and the equipment end verification evidence, and outputting a comprehensive risk level and a recommended disposal action; according to the method, the risk detection can be realized without depending on a decryption key or a differential synthetic material, so that the security of firmware upgrading is ensured, and the operation and maintenance efficiency is also considered.

The application provides an attack path restoration method and device, which can be used in the field of computer technology. The method comprises the following steps: monitoring the running state of an application program in each server and collecting key data of the application program in the running process by using a RASP agent installed on each server; when an attack event is detected, generating an alarm information according to the key data, and determining a target server in each server which has a correlation with the attack event according to the alarm information; generating a server attack path according to the interaction relationship among the target servers; and generating an attack path corresponding to the attack event according to the server attack path and each component in the target server. The application can quickly and accurately restore the attack path of the attack event.

The invention relates to the field of cloud computing and databases, and particularly provides a cloud desktop Linux system restoration method and device, and the method comprises the following steps: S1, mirror image preparation; s2, generating a snapshot; s3, dual-start support is carried out; s4, running period data writing; s5, restoring and triggering; s6, isolating multiple tenants; s7, version upgrading; and S8, performing abnormal protection. Compared with the prior art, the method has the advantages that the cloud desktop restoration capability with second-level restoration, zero network flow and low storage occupation can be realized, and the operation and maintenance complexity and the storage cost are remarkably reduced.

The invention discloses a Dockerfile peculiar smell iterative detection and restoration method and system based on a large language model, and the method comprises the steps: obtaining to-be-optimized initial Dockerfile file content inputted by a user, inputting the to-be-optimized initial Dockerfile file content to a peculiar smell detection module for multi-dimensional scanning and analysis, and outputting structured peculiar smell detection information; fusing a predefined natural language instruction framework, an original Docker file to be optimized and structured peculiar smell information output by a peculiar smell detection module in the iteration to generate a cue word; inputting the cue word into a large language model for semantic analysis and code generation, and outputting an optimized Docker file for the current Docker file odor; and carrying out cleaning and key information extraction on the optimized Dockerfile by adopting a method of combining regular expression matching and semantic analysis, generating Dockerfile update content, and feeding back the Dockerfile update content to the peculiar smell detection module to carry out next round of iteration. According to the invention, intelligence and automation from Dockerfile peculiar smell detection to restoration are realized.

To provide a conversion method and the like capable of reducing power consumption during a memory access with a simple method while maintaining image quality.SOLUTION: First video data is in one or more display line composed by a plurality of pixels being arranged. A conversion method includes: acquisition steps (S11 and S12) of acquiring maximal value and minimum value of gradation value of the plurality of pixels on the basis of the first video data; a determination step (S14) of determining second bit accuracy to be bit accuracy after conversion of the first video data and equal to the first bit accuracy or lower on the basis of the calculated representative value, maximal value and minimum value; a conversion step (S15) of converting the first video data of the first bit accuracy into second video data of the second bit accuracy on the basis of the representative value and the gradation value of the plurality of pixels; and a writing step (S16) of writing the representative value, the second bit accuracy, and the second video data to the memory in association with one another.SELECTED DRAWING: Figure 11

An application restoration method includes displaying a first icon and a second icon on a home screen of a terminal device, where the first icon is an icon of an application and the second icon is an icon of a service widget, uninstalling the application in response to a first operation by a user, displaying a landing page of the service widget and displaying a first control in response to a second operation entered by the user, and installing the application in response to the second operation.

The invention provides a three-dimensional restoration method and device for an object, a storage medium and electronic equipment, and the method is applied to the technical field of computers, and comprises the steps: generating a color image of a target object based on an archaeological drawing of the target object and a photo image of other objects of the same type as the target object, the method comprises the steps of obtaining a color image of a target object, constructing an initial three-dimensional model of the target object based on the color image, obtaining a plurality of key view angle projection structure diagrams for the target object based on a norm division rule of the target object, and carrying out line texture adjustment processing on the initial three-dimensional model based on the key view angle projection structure diagrams and the color image, and obtaining a restored three-dimensional model of the target object. According to the method, the patterns of the target object at other unknown angles can be generated through the division rule expansion of the object, and line texture adjustment processing is performed on the three-dimensional model, so that the overall shape structure, the appearance style and the ornamentation characteristics of the ancient object are restored.

The invention relates to a three-dimensional part color recovery method and device, equipment, a medium and a product. The method comprises the steps of obtaining an initial model file corresponding to a target part; recursive analysis processing is conducted on the initial model file, a topological shape set and a color set are obtained, and the color set comprises colors corresponding to all topological shapes in the topological shape set; obtaining a target assembly structure corresponding to the target part, and constructing a target shape combination based on the topological shape set and the target assembly structure; and performing color mapping processing on the target shape combination by using the color set and the target assembly structure to obtain a color model file corresponding to the target part. By adopting the method, the visualization accuracy can be improved.

The invention provides a metadata restoration method and device, electronic equipment, a storage medium and a program product. The method comprises the steps that a damaged area is determined in a target disk, the damaged area comprises at least one piece of damaged metadata of a target service, and the target service is a service being processed; remapping the logic address corresponding to the damaged area to a temporary area of the target disk, wherein the temporary area is used for storing data corresponding to the target service; performing repair processing on the damaged area to generate at least one piece of repair metadata; and obtaining at least one piece of temporary metadata corresponding to the temporary area, and performing duplicate removal processing on the at least one piece of repair metadata according to the at least one piece of temporary metadata to obtain the target metadata, so that the stability of the storage system is improved.

The invention discloses a multi-source data-driven ecological protection and restoration method and system, and aims to solve the technical problems of contradiction between wetland and forest environment monitoring precision and cost, poor data transmission adaptability, and weak analysis model over-fitting and generalization ability. According to the method, a heterogeneous wireless ad hoc network driven by multi-source data is constructed, and a wireless sensor network and a Mesh network are fused, so that efficient sensing and reliable transmission of wetland and forest land environments are realized; low-cost sensor data is processed by adopting a machine learning and optimization theory, a lightweight environment intelligent detection model is established, an environment-sensitive wireless sensor MAC protocol is optimally designed, and the data transmission efficiency and reliability in a complex environment are improved. According to the method, the monitoring cost can be remarkably reduced, the accuracy and efficiency of ecological environment assessment and pest control and prevention are improved, technical support is provided for ecological protection and restoration, healthy tourism development and digital forest protection, and the method has important application value and social benefits.

This application provides a restoration method, apparatus, electronic device, and storage medium based on a concatenated model, relating to the field of computer technology. The method includes: acquiring a low-quality image; inputting the low-quality image into a pre-trained image quality evaluation large language model to obtain degradation information and semantic information corresponding to the low-quality image, wherein the semantic information includes detailed semantic information and simplified semantic information; retrieving a pre-trained low-frequency restoration model and a high-frequency restoration model; inputting the low-quality image, degradation information, and simplified semantic information into the low-frequency restoration model to obtain a corresponding low-frequency restored image; and inputting the low-frequency restored image and the detailed semantic information into the high-frequency restoration model to determine the corresponding target restored image. This application solves the problem of low image restoration quality in related technologies.

Embodiments of the present application provide a differential file restoration method and an electronic device. In the method, the differential file includes at least one group of data compression blocks, and each data compression block in each group is divided based on a preset block size before compression; when the electronic device restores the differential file, the parallel number k of restoration threads is first determined according to the block size and the RAM space size, and then the differential file is restored in parallel using k restoration threads, wherein each restoration thread uses a group of RAM spaces corresponding to the restoration thread to restore at least one group of data compression blocks. In this way, when the differential file is restored, the electronic device can adaptively determine the parallel number of restoration threads according to the RAM memory space used for differential file restoration, and improve the restoration efficiency of the differential file through parallel processing of multiple threads.

The application provides an image restoration method and device based on artificial intelligence, electronic equipment and computer readable storage medium; the method comprises the following steps: obtaining an image to be restored; performing degradation removal processing on the image to be restored to obtain a latent code feature corresponding to the image to be restored and at least two spatial features of different scales; performing mapping processing on the latent code feature based on at least two latent code networks to obtain at least two latent codes corresponding to the at least two latent code networks one by one; and based on the at least two spatial features of different scales, modulating the prior feature corresponding to the at least two latent codes to obtain a restored image corresponding to the image to be restored. Through the application, the authenticity and credibility of image restoration can be improved.