7results about How to "Reduce storage size" patented technology

A method for extracting key contour points of Chinese characters based on key skeleton points and stroke width belongs to the field of computer and Chinese character vectorization, which comprises the following steps: inputting a single Chinese character picture, performing pretreatment to generate a binary image; extracting the skeleton of the Chinese character by using a skeleton extraction algorithm; further extracting key skeleton points of the Chinese character; obtaining the stroke width at each key skeleton point of the Chinese character; obtaining the contour points of the Chinese character by using a contour extraction algorithm; sequentially traversing all contour points of the Chinese character, calculating the distance from the current contour point to the nearest key skeleton point, calculating the distance threshold of the current nearest key skeleton point, judging whether the current contour point is a key contour point by comparing the distance from the current contour point to the nearest key skeleton point with the distance threshold, and recording the current contour point as a key contour point if the distance is less than the distance threshold. The application effectively improves the quality of Chinese character vectorization, maintains all detail features, effectively removes noise contour points and redundant contour points, and reduces the storage space size of the vectorized Chinese characters.

This invention provides a tube-launched rotor-wing loitering munition and its operating method, comprising a first-stage propulsion device, a deceleration parachute, a second-stage propulsion device, a multi-rotor UAV, a warhead, and a seeker. The beneficial effects of this invention are: The first-stage propulsion device provides initial velocity during launch, enabling rapid deployment. During flight, the first-stage propulsion device can be automatically jettisoned via a mechanism, reducing the weight of the loitering munition and increasing its operational time. The invention also includes a second-stage propulsion device, which further increases the flight speed of the loitering munition, extending its range and compensating for its insufficient operational distance, ensuring the munition quickly reaches a preset altitude and position. For launch-type rotor-wing loitering munitions, by rationally designing the main body structure and the arm extension and retraction structure, the retraction size is significantly reduced, meeting overload requirements and enabling tube-launching of the rotor-wing loitering munition.

This utility model provides a multi-link lifting boom and a boom lifter, belonging to the field of engineering machinery technology. The technical solution of the multi-link lifting boom includes a main boom and a folding boom, as well as a multi-link luffing mechanism. The multi-link luffing mechanism includes a first link, a second link, and a luffing cylinder. The first link has a first end and a second end, and the second link has a third end and a fourth end. The fixed end of the luffing cylinder is hinged to the main boom at a second hinge point. The movable end of the luffing cylinder is hinged to the first and third ends at a third hinge point, and the second end is hinged to the main boom at a fourth hinge point, located away from the folding boom. The fourth end is hinged to the folding boom at a fifth hinge point, located closer to the main boom. This utility model places the fourth hinge point away from the folding boom and the fifth hinge point closer to the main boom, effectively utilizing the space in the hinge area between the main boom and the folding boom, thus reducing the folded size of the boom.

The invention provides a CT (Computed Tomography) reconstruction method, system and equipment of a three-dimensional sparse view angle and a medium. The method comprises the following steps: acquiring projection data formed under a sparse view angle scanning condition and corresponding imaging geometric parameters; determining a ray path set based on the projection data, and carrying out the following processing on each ray path: generating a plurality of three-dimensional sampling point coordinates on the ray path according to imaging geometric parameters corresponding to the ray path; performing feature mapping and interpolation processing on the coordinates of the three-dimensional sampling points based on Hash coding to generate point feature vectors corresponding to the three-dimensional sampling points; inputting each point feature vector into a neural network model to obtain an attenuation coefficient corresponding to each three-dimensional sampling point; carrying out integral accumulation on the attenuation coefficient of each sampling point along the ray direction to obtain a projection result of the ray path; and generating a three-dimensional reconstructed image based on the projection result of each ray path. According to the method, high-quality and low-power-consumption three-dimensional CT reconstruction processing can be realized under the sparse view angle scanning condition.

The utility model discloses a table board subassembly, handrail box device and vehicle relates to vehicle technical field, wherein, table board subassembly includes table board and first support piece, and table board movable installation is in first component of vehicle, and has the far end of support of far away from first component in unfolded state and the near end of support of close to first component, and first support piece rotation is connected in far end of support, and has support position and folding position, in support position, the end of first support piece far away from far end of support is supported by the support action of second component of vehicle, in folding position, first support piece is superposed in table board, the technical scheme provided by the utility model can promote the structural stability of table board in unfolded state.

The invention provides a traceability log storage and query method based on deep embedding and single-layer RNN prediction, and relates to the technical field of traceability graph compression, and the method comprises the steps: converting a system bottom layer audit log into a traceability graph, carrying out the coding mapping of path class and identification class attribute fields through deep learning embedding representation, and obtaining a traceability graph; coding prefixes are distributed for the path type attribute fields and the identification type attribute fields through self-adaptive dictionary coding, and numerical attribute fields are recorded through incremental coding; preprocessing and learning the traceability graph through a single-layer recurrent neural network (RNN) unit; performing local adjustment on the traceability graph during data updating based on incremental coding and adaptive mapping; and mapping the query condition into an attribute coding prefix, reconstructing an attribute sequence based on the attribute coding prefix, and performing correction through the adjustment table. For redundant information and structural similarity, a deep learning embedding representation technology and an adaptive dictionary coding strategy are adopted, and shared codes of similar attribute fields are effectively learned and extracted, so that redundant data storage is reduced.