3results about How to "Overcome size limitations" patented technology

Embodiments of the present invention disclose a camera actuator, comprising: a housing; a mover disposed in the housing and comprising an optical member, and a driving part disposed in the housing to drive the mover, wherein: the driving part comprises a driving magnet, a driving coil placed opposite to the driving magnet, a sensor unit for sensing a position of the mover, and a board unit connected to the sensor unit; the sensor unit comprises a first sensor unit and a second sensor unit opposite to the first sensor unit and connected to the first sensor unit in series.

The application relates to a degradable ZnZrCu alloy with an amorphous-crystal heterostructure and a preparation method thereof, and belongs to the field of material design and preparation. The application proposes a combined process route of mechanical alloying and selective laser melting to in-situ synthesize a ductile phase in an amorphous matrix, and develops a degradable ZnZrCu alloy with both amorphous phase and ductile phase. The medical Zn-based amorphous alloy developed by the application shows good strength-plasticity synergy and good degradation rate. The application inherits the advantages of additive manufacturing of selective laser melting, can effectively break through the size limitation of traditional forming process of amorphous alloy, realize the individual customization of the shape and structure of the amorphous alloy, and provides a new idea for the preparation of the amorphous-crystal heterostructure alloy and biomedical application. Meanwhile, the application is simple in composition, controllable in process, and convenient for large-scale industrial application.

The application discloses a kind of based on unmanned aerial vehicle and deep learning's field crop seedling high-precision detection method.The method is first obtained by unmanned aerial vehicle shooting high-definition remote sensing image, then these images are spliced into DOM image with geographic coordinates by unmanned aerial vehicle image processing software, DOM image is cut, detected, spliced and handled step by step, to obtain the specific location and size information of field crop seedling.Combining data analysis and image processing technology, further obtain field crop seedling information.In the key link of detection and splicing, the application adopts IoA method, which is used to eliminate the errors produced in the detection process of deep learning model and the deviation brought by image cutting process.The results show that, when identifying field crop seedling, the seedling counting accuracy of the method reaches more than 95.3%, and the mAP index is not less than 87.1%.The method provides an effective technical approach for high-precision detection of field crop seedling.