6results about How to "Efficient and accurate generation" patented technology

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 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 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.