3results about How to "Smooth border" patented technology

The present application relates to the technical field of three-dimensional model adaptive voxelization, and particularly relates to a three-dimensional model adaptive voxelization and splitting method and system for complex structures. The method comprises the following steps: obtaining original three-dimensional model data, performing multi-dimensional feature analysis based on the original three-dimensional model data to obtain adaptive voxelization strategy data; performing multi-resolution voxelization on the original three-dimensional model data based on the adaptive voxelization strategy data to obtain initial voxel set data; performing voxel block evaluation based on the initial voxel set data to obtain to-be-split voxel block set data; and performing optimization based on the to-be-split voxel block set data to output split voxel model data. The present application improves the accuracy, efficiency and operability of three-dimensional model processing through three-dimensional model adaptive voxelization and splitting.

The invention discloses a building extraction method based on a high-resolution network, and belongs to the field of image processing and machine vision detection. In order to solve the problems of void phenomenon, poor boundary precision, missing extraction and mistaken extraction of small-sized buildings and the like existing in high-resolution remote sensing image building extraction of an existing deep learning method, the method adopts a multi-stage network optimization strategy: firstly, obtaining a high-resolution building data set; and expanding the training set by adopting a data enhancement technology of sample random rotation transformation, Gaussian filtering boundary enhancement, HSV-based color space transformation and standard deviation-added random Gaussian noise. Sequentially integrating object context representation (OCR) modules on the HRNet backbone network to reduce internal holes; introducing a boundary refinement post-processing Segfix module to carry out direction-guided pixel-level correction on an output boundary so as to optimize the building boundary; a rotary variable-size window attention (RVSA) mechanism is embedded in a down-sampling layer, and the capacity of capturing small target features is enhanced through a dynamically changing window. And finally, end-to-end training is carried out on the constructed model by using an enhanced data set, accurate and complete extraction of the building is realized, and an efficient and reliable solution is provided for scene applications such as urban planning and disaster assessment.

This invention discloses a selective laser atom desorption / removal method for diamond, belonging to the fields of micro / nano manufacturing and atomic-scale manufacturing. The method includes: ion implantation into the diamond region to be removed, causing it to amorphize and form an amorphous carbon region; using the lower laser ablation threshold between diamond and amorphous carbon as the selective desorption threshold; irradiating the amorphous carbon region and the surrounding diamond region with a pulsed laser with an energy density lower than this threshold, utilizing the difference in atomic desorption rates between amorphous carbon and diamond to preferentially remove amorphous carbon until the exposed diamond significantly reduces the desorption rate, achieving self-termination. This invention, through localized amorphization via ion implantation, makes the atomic desorption rate of amorphous carbon more than two orders of magnitude higher than that of diamond, significantly improving processing efficiency; simultaneously, it utilizes the low desorption rate of diamond to achieve self-termination, resulting in controllable processing contours, surface roughness below 1 nm, and no graphite residue or thermal damage.