7results about How to "Anti-aliasing" patented technology

The invention discloses a display panel and a display device, relates to the technical field of display, and can improve the sawtooth feeling of a display picture of a special-shaped display boundary. The display panel includes: a substrate layer; a pixel unit is arranged on one side of the substrate layer, the pixel unit comprises a first sub-pixel, a second sub-pixel and a third sub-pixel, and one pixel unit corresponds to one virtual rectangle; the area proportion of the light-emitting layer in the virtual rectangle is greater than or equal to 80%; connecting lines of geometric centers of all pixel openings in one pixel unit form a virtual triangle, an included angle between a connecting line of geometric centers of pixel openings of the first sub-pixel and the third sub-pixel and a long side of the virtual rectangle is a first included angle, and the first included angle is the smallest included angle between each side of the virtual triangle and the long side of the virtual rectangle; the second overlapping area and the third overlapping area are smaller than or equal to the first overlapping area; a shape of at least one of the pixel openings of the first sub-pixel, the second sub-pixel, and the third sub-pixel includes at least a partial curvilinear edge.

The invention discloses a noise blind source separation method and system for a hydroelectric generating set, belongs to the technical field of acoustic signal processing, and aims to solve the problem that the noise reduction effect of acoustic signals is affected due to the fact that all kinds of noise are difficult to effectively separate by an existing acoustic signal separation method. The method comprises the following steps: firstly, preprocessing actually measured sound signals of a bulb tubular hydroelectric generating set operation site through time domain, frequency domain and time frequency analysis, then carrying out feature analysis by adopting a YOLOv3 network, finally carrying out noise separation by adopting a blind source separation algorithm, and obtaining human voice signals of the operation site based on sound contribution. Therefore, human voice separation and noise reduction processing of actually measured sound signals in a working site are realized.

The invention provides an F-P spectral imaging system and method, and belongs to the technical field of spectral component measurement, and the system comprises a front lens which is used for collecting light energy and converting the light energy into emergent light meeting the limitation of the clear aperture of an F-P interferometer; the annular band optical filter comprises a central area and a plurality of concentric annular areas surrounding the central area, the bandwidth of each area is the same as the free spectral range of the F-P interferometer, and the annular band optical filter is used for eliminating level aliasing in emergent light of the front lens; the F-P interferometer is used for carrying out wavelength selection on emergent light of the annular band optical filter and outputting an interference field; the imaging mirror is used for projecting the interference field to the detector; and the detector is used for converting the projected optical signal into a digital electric signal. The F-P spectral imaging system which can maintain high spectral resolution and also can realize wide spectrum coverage is constructed by introducing the annular band optical filter which is accurately matched with the FSR of the F-P interferometer.

This application discloses a deep learning-based intelligent monitoring method and system for surface cracks in bridge structures. First, it performs spatiotemporal alignment and heterogeneous fusion of multi-source sensor data, then utilizes a dual-stream deep neural network to extract the probability distribution features and pixel-level extension direction fields of the cracks in parallel. Based on this, by introducing a directionally regularized potential energy field and a non-maximum suppression mechanism, high-precision skeleton extraction conforming to hydrodynamic characteristics is achieved. Furthermore, this scheme transforms the visual perception space into a graph theory space, constructing a connection cost matrix based on crack breakpoints and their local tangent directions, and using a minimum spanning tree algorithm to intelligently stitch together visually broken but logically connected paths. Finally, by combining depth information to invert the true physical size and hazard level of the cracks, it achieves a leap from simple image segmentation to physical structural integrity assessment, ensuring the topological authenticity and engineering usability of the monitoring results.

This application proposes an obstacle edge contour recognition method and system based on LiDAR point cloud data, belonging to the field of edge contour recognition technology. The method includes: accurately selecting effective voxels and intelligently marking transition regions through a dual judgment mechanism of voxel mesh division and internal dispersion index to construct a high-purity candidate dataset; generating a high-precision feature point set by combining principal component analysis of local point cloud slices with reflection intensity and depth information; and smoothing and optimizing the contour through a quadratic Bézier curve and nearest projection point correction algorithm, ultimately constructing a time-series iterative optimization closed loop including breakpoint identification, historical data replacement, and interpolation completion, outputting an optimized edge contour with a rigorous topological structure and geometric continuity. This solves key problems in existing technologies such as high noise interference, limited geometric feature description, severe contour breakage and overlap in dynamic scenes, and discontinuous trajectories.

The invention discloses a high-quality jet printing method and system, electronic equipment and a medium, and relates to the technical field of industrial ink jet printing. The method is applied to a high-quality jet printing system comprising a first spray head and a second spray head which are physically aligned and have a physical dislocation distance in the direction perpendicular to the medium movement direction. Firstly, a logic image under a target resolution is acquired, and pixel points are allocated to a first nozzle and a second nozzle according to a preset allocation rule, such as a diagonal staggered distribution or edge optimization allocation strategy. And then, the movement speed of the printing medium is obtained in real time, the first spray head is controlled to conduct jet printing at the reference moment, real-time trigger delay is calculated according to the physical dislocation distance and the real-time movement speed, and the second spray head lags behind the delay to conduct jet printing. Through the space-time cooperative control, the ink droplets jetted by the two nozzles with lower physical resolutions form a dot matrix distributed in a staggered manner on the printing medium, and a printing image equivalent to a target high resolution is synthesized.

A neural network system is provided that implements a generative model for autoregressively generating a distribution of a plurality of current filterbank samples of an audio signal, where the current samples correspond to a current time bin, and each current sample corresponds to a channel of the filterbank. The system includes a hierarchy of a plurality of neural network processing layers ordered from a top layer to a bottom layer, each layer trained to generate conditioning information based on previous filterbank samples, and for at least each layer other than the top layer, also based on conditioning information from a higher layer in the hierarchy; and an output stage trained to generate a probability distribution based on previous samples of one or more previous time bins and conditioning information from the lowest processing layer.