4results about How to "Achieve high-precision recognition" patented technology

This application discloses a method, device, and storage medium for air gesture recognition, relating to the field of gesture recognition technology. The method includes: acquiring reflected signals after a hand gesture reflects a target acoustic signal through at least one microphone in a wearable device, wherein the target acoustic signal is constructed from a signal emitted by at least one speaker in the wearable device; performing frequency domain processing on each reflected signal to obtain target time-series spectrum information; performing differential processing on each target time-series spectrum information to obtain differential spectrum information; extracting potential gesture segments based on each differential spectrum information; inputting each potential gesture segment into a pre-constructed gesture recognition model, and outputting gesture recognition results. This application can improve the accuracy of gesture recognition during interaction.

The application discloses a kind of power equipment defect identification and warning method and system based on deep learning.The method comprises: synchronously collecting and registering the visible light and infrared thermal imaging image on the surface of power equipment, constructs the instance segmentation network including light weight feature extraction network, multiscale feature fusion network and frequency domain mask prediction branch;Adopt the generative adversarial strategy to enhance the diversity of training sample;Based on graph neural network, analyze the association between defect and equipment topology, historical record, infer the cause-effect relationship of defect and risk level;Generate the interpretable warning information including heat map, natural language report and repair suggestion;Real-time detection and deep analysis are realized using end-edge-cloud collaborative architecture;Through closed-loop optimization mechanism, continuously improve system performance.The application realizes high-precision defect detection under multi-modal data fusion, has strong robustness and interpretability, significantly improves the intelligent level of power equipment operation and maintenance.

This invention discloses a pure vision-based 3D reconstruction and adaptive completion method in a collapse environment, belonging to the field of computer vision and emergency rescue 3D reconstruction technology. The method completes initial 3D reconstruction by acquiring data through binocular vision, constructs an anisotropic point cloud density distribution field to achieve accurate detection of low-density blind spots, establishes safe and reachable spatial constraints based on an implicit distance field, and optimizes the completion viewpoint by fusing an observability model. Map iteration is completed through local reconstruction and point cloud updates, and a closed-loop completion mechanism is formed using point cloud density as feedback until the reconstructed model meets the integrity requirements. This invention solves the problems of permanent voids in reconstruction caused by viewpoint blind spots, poor consistency between completion results and the real scene, and insufficient safety in the reconstruction process in existing technologies in collapse environments. It can achieve complete and high-precision autonomous reconstruction of 3D models of collapse disaster sites, providing reliable spatial data support for emergency rescue decision-making.

The application provides a half-height-width region identification method and system based on linear interpolation. The method comprises the following steps: obtaining two-dimensional topography data of a target structure prepared by a scanning probe nanometer direct writing; extracting a height data sequence of a single-row topography from the two-dimensional topography data; identifying key feature points in the height data sequence; calculating left half-height position height values and right half-height position height values based on the key feature points; determining left half-height-width boundary positions corresponding to the left half-height position height values and right half-height-width boundary positions corresponding to the right half-height position height values by using a linear interpolation method; and taking a difference value between the left half-height-width boundary positions and the right half-height-width boundary positions as a half-height-width value corresponding to the current single-row topography. The technical scheme provided by the application realizes automatic and high-precision identification of nanometer structure feature sizes, and significantly improves the measurement efficiency and the objectivity of process analysis.