9results about How to "Achieve segmentation" patented technology

The utility model relates to an anti-ice-falling device for the surface of a cross tie beam of a bridge tower, which comprises a plurality of anti-ice-falling devices arranged on the surface of the cross tie beam, each anti-ice-falling device comprises an anti-ice-falling clamp, a plurality of raised fixing pieces and a plurality of extended connecting pieces, and the anti-ice-falling clamps comprise a first anti-ice-falling clamp and a second anti-ice-falling clamp. The first anti-ice-falling clamp and the second anti-ice-falling clamp are fixedly arranged on the edges of the left side and the right side of the cross tie beam respectively, and the first anti-ice-falling clamp and the second anti-ice-falling clamp are connected into a whole through the extending connecting pieces and the protruding fixing pieces and fixed to the upper surface of the cross tie beam. The limiting baffles arranged at certain intervals prevent solid accumulated ice from sliding on the upper surface of the bridge tower cross tie beam, meanwhile, lateral drainage of the upper surface of the cross tie beam cannot be hindered, the phenomenon that a traditional drainage channel becomes a'water blocking channel 'due to icing is avoided, and the size of a single block of ice accumulated on the upper surface of the cross tie beam is limited within a safety threshold value as much as possible.

The application discloses a kind of complex lighting conditions underwater artificial crack dataset construction method, it is related to image dataset production technical field, including, collection crack picture and extract crack curve generation coordinate information, based on this, construct crack 3D model and prepare concrete standard test block;The test block is placed in water, and underwater crack image under conventional, dim and uneven illumination is collected, and is classified after pre-processing according to illumination condition;Stable Diffusion model based on LoRA fine-tuning is used, and different illumination condition images are input respectively to train and optimize, and style expansion image is generated, and pre-processing image constitutes unlabeled data together;Through image enhancement algorithm processing the data, after the enhanced image is labeled, the label is corresponded with the original image, and the underwater artificial crack dataset under complex lighting conditions is constructed, the application solves the problem that actual underwater crack disease is difficult to collect, meets the core demand of engineering practice, and provides richer data support for underwater structure crack detection and segmentation model training.

In order to solve the problems of limited labeled data, differences between blood vessels and interference of lesion area, the present application discloses a retinal blood vessel image segmentation method based on a multi-scale dilated convolution residual network, which is still a challenge problem for accurately segmenting retinal blood vessels, especially fine blood vessels, on a retinal fundus image. The present application designs a multi-scale residual input and output module to make up for the loss of part of the blood vessel structure information due to down-sampling, combines the advantages of dilated convolution and DropBlock to relieve network overfitting and reduce the influence of the lesion area on blood vessel feature extraction, and further introduces a multi-scale mean pooling module to obtain high-level features and retain context information. Finally, by improving the way of jump connection, the dilated convolution is effectively used to improve the information transmission capacity of the jump connection. Compared with other algorithms, the present application can more accurately segment the fine blood vessels in the retinal image under complex conditions and has better robustness.

The application discloses an AI identification method, system and model training method for millimeter wave image overlapping targets based on a three-branch network, and solves the security target detection problem in millimeter wave images with low resolution, mutual interference or mutual overlap through collaborative work of three independent branch networks, namely, an analysis branch network, an aggregation branch network and a prediction boundary branch network. The analysis branch network saves the detailed information in a high-resolution feature map; the aggregation branch network realizes the feature position offset alignment of high and low resolution feature maps through a recursive fusion module; and the prediction boundary branch network extracts high-frequency features and enhances the perception and prediction of target edges. The multi-branch network structure effectively realizes the segmentation and identification of images through the fusion between branches. While improving the segmentation performance of the model, the model significantly reduces the calculation complexity and the detection error and missed detection probability in millimeter wave images, and finally realizes the accurate detection of overlapping objects.

The invention relates to an etching method and a semiconductor manufacturing method, and the etching method comprises the steps: depositing a first oxidation layer and a first mask layer on a to-be-etched layer, forming a plurality of metal channels in the first mask layer through patterning, depositing a mask layer group on the first mask layer, and carrying out the etching of the mask layer group through patterning, so as to form a mask block, and etching the first oxide layer and the to-be-etched layer by taking the first mask layer and the mask block as masks to form a target pattern. And etching the first oxide layer and the to-be-etched layer by taking the first mask layer and the mask block as masks, thereby obtaining the target pattern on the to-be-etched layer, realizing segmentation of the metal layer in the target pattern, realizing effective insulation between the metal layers, reducing function failure caused by crosstalk or short circuit between the metal layers, and improving the performance of the device. Therefore, the overall performance and reliability of the chip are improved, and the production rate of defective products is reduced.

The invention relates to an image processing method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring an image acquired by a robot; performing semantic segmentation and mask generation on the image to obtain a task area, a non-task area and mask image data of the non-task area; performing disturbance processing on the non-task area to obtain a disturbed non-task area; and based on the task area, the post-disturbance non-task area and the mask image data, generating a target image for robot imitation learning. By adopting the method, the problem of distraction in the imitation learning process can be effectively avoided.

This invention relates to the field of computer technology and discloses a method, apparatus, device, and storage medium for developing web pages. The method includes: receiving a web page development request; responding to the request by invoking a pre-built business code library and a pre-built component code library; generating a web page framework based on the business code library; performing conversion processing on the component code library to generate component links corresponding to the component code library; introducing the component links into the web page framework; and generating the web page using the Render function of the Vue framework library. Through this method, the invention can achieve the separation of component code and business code, eliminating the need for further separation of component code, reducing code coupling among multiple developers and departments, lowering communication costs and maintenance management risks, improving page development efficiency, and solving the problem of low web page development efficiency caused by developers repeatedly reviewing code when collaborating with multiple people and departments.

This invention discloses a method and system for obtaining thread profile parameters, belonging to the field of data processing technology. The method involves performing continuous wavelet transform on the profile signal to extract the energy distribution and periodic characteristic frequencies of the thread's characteristic frequency band. Multiple local statistical features of the energy distribution are obtained, and adaptive threshold functions for the thread start boundary, end boundary, and complete thread are constructed through different combinations of these local statistical features, corresponding to the identification of the thread start position, end position, and the entire effective thread range. Within the effective range of the complete thread, the profile signal is bandpass filtered in the frequency domain to extract the main frequency components corresponding to the thread's periodic characteristics, and the filtered frequency domain signal is obtained. The purified profile signal is reconstructed through inverse Fourier transform, and the pitch is determined using an instantaneous frequency tracking method, the tooth height is determined using an amplitude analysis method, and the thread taper is determined using low-frequency energy feature analysis. This method enables intelligent identification and precise segmentation of the thread region.

The application discloses a panoramic camera auxiliary-based GNSS non-line-of-sight signal identification and application method, constructs a light MN-DLV3-CRF model to optimize the boundary information, obtains a clear segmentation boundary, and constructs a sky map with shielding information; the sky map is divided into at least a non-shielding sky area, a building shielding area and a tree shielding area according to the segmentation boundary; when a satellite signal falls into the building shielding area and the tree shielding area, the satellite signal is determined as an NLOS signal; if the satellite signal falls into the tree shielding area, the NLOS weight of the tree is calculated by considering the NLOS weight model of the tree. The method generates a shielding sky map by semantic segmentation of a sky image, assists a GNSS receiver in identifying NLOS signals shielded by buildings, trees and the like, improves positioning precision in complex scenes such as urban canyons and shaded roads, and is suitable for high-precision positioning scenes such as vehicle navigation, unmanned aerial vehicle positioning and intelligent transportation systems.