9results about How to "Improve automated processing performance" patented technology

The invention belongs to the technical field of satellites, and discloses a centralized photovoltaic power station capacity prediction method and system based on a satellite image and topographic data, and the method comprises the steps: carrying out the recognition of a Sentinel remote sensing image, obtaining a photovoltaic distribution position after photovoltaic automatic recognition according to the spectral characteristics, including the mean value of each spectral band, NDVI, NDWI and other indexes, and carrying out the prediction of the capacity of a photovoltaic power station. Meanwhile, elevation data provided by DEM images are integrated to calculate a topographic slope value, then influence factors such as photovoltaic image area, inclination angle, direction angle and installation spacing are calculated by using parameters such as image resolution and geographic latitude, and finally, parameters such as known photovoltaic scale and photovoltaic materials are combined to obtain a photovoltaic power generation system. And a prediction model of the capacity of the centralized photovoltaic power station is constructed with the installation capacity of a small number of known photovoltaic power stations, so that accurate prediction from the image area of the photovoltaic power station identified by the satellite image to the actual installation capacity is realized. The method comprehensively considers the influence of the direction angle, the inclination angle, the installation spacing and the like of the photovoltaic power station on the actual installation capacity, is suitable for mountainous and hilly areas with complex terrains, improves the problem of inaccuracy of a method for estimating the capacity based on the projection area, and provides a scientific basis for the capacity evaluation of the photovoltaic power station.

The invention provides a remote sensing image segmentation method and device, and belongs to the technical field of image processing, and the method comprises the steps: extracting a feature map of an input image through an image encoder; obtaining a similar feature graph of the feature graph and each reference sample feature in a pre-created reference sample library; selecting a target similar feature map with the maximum similarity peak value from all the similar feature maps, and inputting the target similar feature map into a prompt embedding generation network to generate prompt embedding; the prompt embedding generation network is a pre-constructed convolutional neural network; and inputting the prompt embedding and the input image into an image decoder, and outputting a segmentation result. According to the remote sensing image segmentation method and device provided by the invention, the adaptability to data in a specific field is enhanced, a high-degree automatic processing flow is also provided, prompt embedding can be automatically generated, and prior prompt is not needed.

The invention discloses a bidding document title structure extraction method based on an OCR engine. The bidding document title structure extraction method comprises the steps that a bidding document in a pdf format is converted into an image file; performing text content recognition on the bidding document image file by utilizing OCR (Optical Character Recognition); sorting bidding document character recognition results according to the text block position information of the OCR recognition results, and obtaining bidding document text contents; performing title structure extraction on the paragraph content of the bidding document text; optimizing the title paragraphs by using header and footer rules and title features; the method solves the problems of low efficiency and strong manual dependence in the prior art, can quickly and accurately extract the title information of the document, improves the title extraction efficiency and accuracy, and is suitable for various types of documents.

The invention discloses a geological radar image automatic identification method and device and a medium, and relates to the technical field of image processing, and the geological radar image identification process comprises data acquisition, preprocessing, 3D point cloud fusion, semantic segmentation, neural network processing and real-time monitoring. The method comprises the following steps of: firstly, collecting geological radar image data and preprocessing the geological radar image data to generate sample data of which noise in an image is removed, then fusing the sample data into a 3D point cloud, and carrying out semantic segmentation to obtain multi-modal data; thirdly, inputting the data into a neural network model, and extracting a single-stage target detection feature map; then, the feature map is sent to a candidate region generation network, and a depth feature map of the detection target is obtained; and finally, identifying the position and category of the target based on the depth feature map, carrying out real-time monitoring, and outputting an identification result. According to the process, the recognition precision and efficiency are improved, manual intervention is reduced, and data multi-modality and algorithm robustness are enhanced.

The utility model discloses a cooling mechanism for metal piece heat treatment processing, which comprises a base and a steam generator arranged at the top of the base, an adjusting structure is arranged at the top of the base, the adjusting structure comprises a corrugated pipe fixedly connected to the top of the base, the top of the corrugated pipe is fixedly connected with a top cover, and the top cover is fixedly connected with the top of the base. And the steam generator is communicated with the top of the top cover. The push plate is pushed through the transmission structure, the push plate is extruded and swings with the pin shaft as the axis, the push plate extrudes the top cover in the swinging process, the top cover pulls the corrugated pipe to stretch, the inner space is adjusted, and after the corrugated pipe is adjusted, the steam generator is started and fills steam into the space for cooling. According to the utility model, the size of the spraying space in the comparison file can be flexibly adjusted, so that the whole spraying space can be quickly filled with steam, the breakage speed of a steam film is prevented from being increased, and the part storage effect is ensured.

The invention belongs to the technical field of artificial intelligence and management, and relates to a claim settlement intention recognition method and device, computer equipment and a storage medium, and the method comprises the steps: carrying out the intention recognition of a to-be-recognized insurance claim settlement text through employing a trained claim settlement intention recognition model, and obtaining a claim settlement intention type; determining a claim settlement processing flow corresponding to the to-be-identified insurance claim settlement text according to the claim settlement intention category; wherein the claim settlement intention recognition model performs error correction processing on insurance claim settlement text data for training based on a pointer network model guided by a confusion set; performing claim settlement intention data expansion according to the insurance claim settlement text data after error correction by adopting a hybrid generation model combining a generative adversarial network and a variational auto-encoder; and performing model training based on the insurance claim settlement text data after error correction and the expanded claim settlement intention data. The claim settlement intention can be efficiently identified under the small sample condition.

The present invention provides a remote sensing image segmentation method and device, belonging to the field of image processing technology, the method comprising: extracting a feature map of an input image using an image encoder; obtaining a similar feature map of the feature map and each reference sample feature in a pre-created reference sample library; selecting a target similar feature map with the largest similarity peak from all similar feature maps, and inputting the target similar feature map into a prompt embedding generation network to generate a prompt embedding; the prompt embedding generation network is a pre-built convolutional neural network; inputting the prompt embedding and the input image into an image decoder, and outputting a segmentation result. The remote sensing image segmentation method and device provided by the present invention enhances the adaptability to data in a specific field, and also provides a high degree of automated processing flow, which can automatically generate prompt embedding without prior prompts.

The utility model discloses a kind of oil and gas field produced water treatment standard detection devices, it is related to environmental protection engineering technical field, including filter box and detection box, the filter box upper end is equipped with multi-point rain distributor, the multi-point rain distributor is equipped with inlet pipe, the filter box lower end is equipped with drain pipe, the drain pipe is connected with detection box one end by connecting assembly, the detection box other end is equipped with drain pipe, and circulation assembly is equipped between the drain pipe and the inlet pipe;Gravel layer, quartz sand layer, PES filter material layer, magnetite layer and modified fiber ball layer are installed in the filter box by mounting assembly;The utility model passes through the filter material layer structure and gradation in optimization filter box, solve the problem that traditional filter material combination is easily mixed, and the problem of insufficient sewage interception capacity, by setting circulation assembly, realize the secondary filtration treatment of water sample that does not reach standard, solve the drawback that traditional device needs manual intervention when single filtration does not reach standard.

This invention belongs to the field of artificial intelligence technology and relates to a multi-agent recursive task decomposition and adaptive routing method and system. The main steps of this method include task reception and semantic parsing, recursive task decomposition and task dependency graph construction, agent dynamic matching and adaptive routing, knowledge gap identification and "illusion" suppression mechanism, fault-tolerant scheduling and task rerouting, subtask result aggregation and closed-loop evaluation feedback. This invention comprehensively improves the automation, accuracy, and reliability of complex task processing by integrating recursive automatic task decomposition, agent dynamic routing, adaptive knowledge completion, a robust fault-tolerant mechanism, and a result feedback optimization mechanism. It is particularly suitable for complex knowledge processing scenarios such as in-depth interpretation of policy documents, multi-dimensional scientific research information evaluation, and review of large-scale project materials, and has significant technical advantages and broad application prospects.