12results about How to "Efficient and accurate generation" patented technology

The invention relates to the technical field of document search, and discloses a document question and answer method, device and equipment and a storage medium, the method comprises the following steps: receiving a question entry and document identification information input by a user, and obtaining document segments of a target document corresponding to the document identification information; calculating semantic relevancy between the question entry and each document segment, and selecting a to-be-input document segment of which the semantic relevancy reaches a preset relevancy from each document segment; and inputting the question entry and the to-be-input document segment into a pre-training language model, so that the pre-training language model generates an answer of the question entry based on the target document segment. According to the method, the question entries and the to-be-input document with the semantic relevancy reaching the preset relevancy are input into the pre-trained language model in a segmented mode, and compared with the situation that answers cannot be efficiently generated when the whole document is input in the prior art, the answers of the question entries are accurately and efficiently generated, and the user experience is improved. And the user experience is effectively improved.

The invention discloses an operation analysis report generation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining user attention information and original data of a to-be-analyzed production operation project, and obtaining a target dimension index based on the original data; according to the user attention information, background purpose analysis data is generated based on the target dimension index by using a preset large language model; according to the target dimension index, carrying out drilling analysis on the original data based on the time trend and the code value to obtain a numerical analysis result; and based on the background objective analysis data and the numerical analysis result, performing data integration by using a preset large model to obtain an experience analysis report. According to the method, the operation data is automatically processed and analyzed through the large language model, and the operation analysis report is obtained by utilizing the text understanding and generating capability of the large language model. The method can efficiently and accurately realize operation analysis report generation, and can be widely applied to the technical field of data processing.

The invention discloses an image generation method and device, a model training method and device, electronic equipment and a computer readable storage medium. The method comprises the steps of obtaining product description information and a product pattern corresponding to a target product of a to-be-generated display graph; generating background image description information corresponding to the product description information through a pre-trained text generation model based on the product description information; and based on the product pattern, through a pre-trained text guide image generation model, and by taking the background image description information as a guide text of the text guide image generation model, generating a display image for adding a background to the product pattern. Through the scheme provided by the invention, the high-quality display graph with the background matched with the product is more efficiently generated, and meanwhile, the labor cost required by background generation is saved.

The present disclosure relates to systems, methods, and non-transitory computer-readable media for performing interactive digital image editing operations with machine learning models and feature backpropagation refinement layers. For example, the disclosed systems perform interactive digital image editing operations by incorporating a feature backpropagation refinement layer into a non-interactive machine learning model that utilizes a consistency loss to adjust the feature backpropagation refinement layer according to one or more user interactions. In some embodiments, the disclosed systems utilize a feature backpropagation refinement layer that includes a bias sublayer for localizing changes to a digital image and a convolution sublayer for per-channel scaling and feature combination across channels. In some cases, the disclosed systems utilize a consistency loss that facilitates localized modifications to a digital image based on a distance of various pixels or features from a user interaction.

Embodiments of the present disclosure disclose a resource warning method and device based on a computing node cluster and an electronic device. A specific implementation of the method comprises: determining whether to call the computing node cluster for resource processing; for each interactive object, determining the corresponding model calculation amount in the information prediction process; selecting a first computing node from the computing node cluster to support the call of each interactive object; for each interactive object, generating first historical resource overdue summary information and first future resource overdue summary information; generating second historical resource overdue summary information and second future resource overdue summary information; generating target resource quality information; and sending corresponding encrypted information to a target monitoring terminal to perform target warning under the condition that the resource quality warning condition is met. The implementation accurately and efficiently generates target resource quality information on the basis of reducing waste of computing resources through reasonable allocation of hardware resources.

The invention relates to an intelligent scheme filling method and device based on a programming language and computer equipment. The method comprises the following steps: in response to a selection operation for at least one scheme element, obtaining a scheme element matched with the selection operation as a target scheme element; the target scheme element is used for describing at least one of test equipment, operation items, instruments and meters and working members corresponding to the working scheme; according to a preset first mapping relation and the target scheme elements, determining operation requirement information used for representing operation requirements corresponding to the working scheme; the preset first mapping relation is used for representing the corresponding relation between the scheme elements and the operation requirements; and generating working scheme information for representing the working scheme according to the target scheme element, the operation requirement information and a preset template. By adopting the method, the working scheme can be accurately and efficiently compiled based on the scheme elements selected by the user and the operation requirements corresponding to the scheme elements, so that the generation efficiency of the working scheme is improved.

The invention belongs to the technical field of power distribution network operation and control, and particularly relates to a power distribution network topology switching path generation method and system based on loop matching, and the method comprises the steps: accurately obtaining a to-be-closed branch and a to-be-disconnected branch of a topology network through the structural difference between an initial topology structure and a target topology structure; the perfect matching between each to-be-closed branch and each to-be-disconnected branch is obtained by constructing the operation bipartite graph, and the complex topology constraint relationship between the branches can be converted into the matching and sorting problem in the graph theory, so that the computing power consumption in the topology switching path acquisition process can be obviously reduced; therefore, the generation efficiency of the topology switching path can be improved; through the timing constraint graph and topology connectivity verification, the non-executable topology switching paths can be screened out, so that the feasible topology switching paths can be accurately reserved. Therefore, the method and the system provided by the invention can efficiently and accurately generate the feasible topology switching path.

The invention belongs to the technical field of artificial intelligence, and relates to an artificial intelligence-based image analysis method, which comprises the steps of performing feature extraction on a first image and a second image, and obtaining a first feature pyramid and a second feature pyramid; performing semantic segmentation to obtain a first semantic probability graph and a second semantic probability graph; performing attention generation on the first semantic probability graph and the second semantic probability graph to obtain a first attention weight graph and a second attention weight graph; respectively generating a first foreground exclusion confidence coefficient and a second foreground exclusion confidence coefficient based on the first semantic probability graph and the second semantic probability graph; and performing similarity calculation on the first feature pyramid, the second feature pyramid, the first attention weight map, the second attention weight map, the first foreground exclusion confidence coefficient and the second foreground exclusion confidence coefficient to generate background similarity. The method can be applied to image similarity analysis scenes in the financial science and technology field and the digital medical field, and the accuracy of image background similarity calculation is improved.

This application belongs to the field of artificial intelligence technology and relates to an AI-based image processing method, apparatus, computer device, and storage medium. The method includes: acquiring input text description and a reference image; extracting features from the text description and reference image using a hierarchical encoder to obtain a text embedding corresponding to the text description and a pose embedding corresponding to the reference image; performing semantic alignment processing on the text embedding and pose embedding using a hierarchical alignment module to obtain alignment features; performing semantic optimization processing on the alignment features using a cross-modal adapter to obtain target features; performing image generation processing corresponding to the target features using a pose condition generator to obtain a target image; and outputting the target image. Furthermore, the target image of this application can be stored in a blockchain. This application can be applied to text-to-image scenarios in the financial and medical fields, achieving precise pose control from text to image and improving the quality of the generated target image.

The invention belongs to the technical field of artificial intelligence, and relates to an artificial intelligence-based speech synthesis method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a to-be-synthesized target text; performing feature conversion on the target text based on a conversion network in a preset target speech synthesis model to obtain acoustic features; converting the acoustic features based on an acoustic mode encoder to obtain an acoustic embedding sequence; adjusting the length of the acoustic embedding sequence based on a phoneme duration adapter to obtain a target embedding vector; fusing the target embedding vector and a preset target style feature based on a style decorator to obtain fused embedding; performing Mel spectrogram generation on fusion embedding based on a Mel spectrogram encoder and a linear layer to obtain a target Mel spectrogram; and performing voice conversion on the target Mel-frequency spectrogram based on a vocoder to obtain target voice. In addition, the target voice may be stored in the blockchain. According to the invention, natural, accurate and high-quality target voice can be efficiently and accurately generated.

The present disclosure provides an OFD document generation method, device and equipment and storage medium, relates to the technical field of artificial intelligence, in particular to the technical field of image processing, computer vision, deep learning and the like. The OFD document generation method comprises: acquiring a document image, the document image containing a target object; performing layout analysis on the document image to obtain layout information of the target object; performing layout analysis on the document image based on the layout information to obtain object information of the target object and determine a reading order of the target object; and adding the object information of the target object to a blank OFD document based on the reading order of the target object to obtain a target OFD document. The present disclosure can accurately and efficiently generate an OFD document.

The present invention relates to the technical field of nursing medical record generation, and in particular to a method and system for generating a nursing medical record. In the present invention, a nursing medical record template library and patient text data are collected; the patient text data and the nursing medical record template are converted into vectors through a bidirectional text vectorization model, and template matching and field filling are realized by cosine similarity calculation. This method solves the problems of insufficient semantic understanding, inaccurate template selection and inaccurate information filling in traditional medical record generation. By calculating the similarity between the average text word vector and the template vector, the most suitable medical record template is accurately selected; and by calculating the similarity between each field and the text vector, a semantic correlation list is generated to realize intelligent filling.