41results about How to "Improve mapping ability" patented technology

Systems and methods for modifying the number of texture samples used to produce an anisotropically filtered texture mapped pixel may improve texture mapping performance. When the number of texture samples is reduced, fewer texels are read and fewer filtering computations are needed to produce a texture value for an anisotropic footprint. The number of texture samples is reduced based on the mip map level weight. The number of texture samples may also be modified using specific parameters for the coarse and / or fine mip map levels. The spacing between the texture samples along the major axis of anisotropy may be modified to improve image quality or texture cache performance.

The invention provides a mapping method and a mapping device for a coarse-grained reconfigurable password logic array so as to simplify a mapping process. The coarse-grained reconfigurable password logic array comprises reconfigurable processing units PE which are fully interconnected; the method comprises the following steps: dividing operation nodes in a cryptographic algorithm data flow graph into a plurality of operation clusters; taking PE in the coarse-grained reconfigurable password logic array as an ant node, and calculating by using an ant colony algorithm to obtain an optimal mappingpath between the coarse-grained reconfigurable password logic array and an operation cluster; wherein each PE in the optimal mapping path is mapped with one operation cluster. Visibly, in the embodiment of the invention, the cryptographic algorithm data flow graph is divided in advance, and then mapping is performed based on the operation cluster, so that the mapping granularity of the cryptographic algorithm data flow graph is increased, and the algorithm mapping complexity is correspondingly reduced. Meanwhile, the mapping between the coarse-grained reconfigurable password logic array and the operation cluster is completed by adopting an ant colony algorithm, the mapping convergence process can be accelerated, and the mapping performance and efficiency are improved.

The invention discloses a liquid crystal base image and wavefront dual-mode electrical-modulation imaging detection chip, and the chip comprises a liquid crystal micro-optical structure, an area-array visible-light detector and a drive control preprocessing module; the liquid crystal micro-optical structure is an area-array electronic control liquid crystal micro lens under a sequential power-up state; the area-array visible-light detector is divided into a plurality of sub-area array visible-light detectors by the area-array electronic control liquid crystal micro lens according to the array size thereof, and each unit of the electronic control liquid crystal micro lens matches one sub-area array visible-light detector to form a wavefront measurement mode; the liquid crystal micro-optical structure is a liquid crystal phase plate for delaying an incident wave beam under a sequential power-off state, and the liquid crystal phase plate and the area-array visible-light detector form an imaging mode. According to the invention, the chip can capture the emerging wavefront and a high image quality flat image of a target based on a sequential electric signal, the detection efficiency is high, the chip is easy to use and couple with a conventional imaging optical system.

The present invention relates to a BP neural network-based anti-dazzle glass chemical erosion technological parameter optimization method. The method comprises the following steps of S1 processing data; S2 determining an optimization range of the erosion temperature and the erosion time; S3 utilizing a BP neural network to construct a relation model of the erosion temperature, the erosion time and the glass transmittance; S4 carrying out the BP neural network optimization search. According to the present invention, the BP neural network is utilized to optimize an anti-dazzle glass chemical erosion technological parameter, and the BP neural network has the high mapping capability, so that any nonlinear mapping from input to output can be realized. By utilizing the high mapping capability and generalization capability of the BP neural network to establish a nonlinear relation of the temperature, the time and the transmittance, a parameter optimization problem influenced by complicated factors can be solved.

The embodiment of the invention discloses a text mapping model processing method and device, computer equipment and a storage medium, and belongs to the technical field of computers. The method comprises the steps of obtaining sample text information and first label information, and mapping the sample text information based on a text mapping model to obtain predicted text information; and determining second label information based on a first similarity between the predicted text information and the sample text information and a second similarity between the first label information and the sample text information, and training the text mapping model based on the second label information, the predicted text information and the first similarity corresponding to the predicted text information. In the embodiment of the application, the text information most similar to the sample text information is taken as the second label information, and the text mapping model is trained based on the predicted text information, the second label text information and the first similarity between the predicted text information and the sample text information, so that the mapping effect of the text mapping model is improved.

The invention discloses a traffic mapping method for a time-sensitive network, comprising the following steps: a first device sends a request message to a network controller according to an IP address of a second device to obtain a TSN label; the first device writes the TSN label into the IP-MAC table; the first device communicates with the second device according to the IP address and TSN label of the second device. In this technical solution, when the first device accesses the peer communication device in the TSN network, it only needs to call the TSN label obtained from the network controller and stored in the IP-MAC table combined with the IP address of the peer device. Communication between the first device and the peer device. There is no need to add a TSN label to each communication data packet, which avoids the degradation of traffic mapping performance caused by this processing method. Therefore, the technical solution is simple and convenient, and can significantly improve network traffic mapping performance.

The invention relates to a strong mapping digital twin system based on a virtual imaging technology. According to the system, a multi-information cooperative communication mechanism is established between digital twin bodies, morphological information, state information and behavior information of a physical entity system are collected through multiple sensors and sent to an edge computing node, and the edge computing node is responsible for receiving sensor information and carrying out edge computing processing on the received information; A virtual imaging technology is applied to project digital entities of the digital twin system into a real space in a three-dimensional visualization mode, meanwhile, state information of the physical entities is displayed in a virtual reality mode, thedetail display effect of the digital twin system is enhanced, and the requirements for multi-view observation and immersion experience are met; According to the system, strong information mapping isestablished between a physical entity and a digital entity through the process, and it is guaranteed that information is transmitted between twin bodies in real time at a high speed in an undistortedmode.

The present invention relates to a BP neural network-based anti-dazzle glass chemical erosion technological parameter optimization method. The method comprises the following steps of S1 processing data; S2 determining an optimization range of the erosion temperature and the erosion time; S3 utilizing a BP neural network to construct a relation model of the erosion temperature, the erosion time and the glass transmittance; S4 carrying out the BP neural network optimization search. According to the present invention, the BP neural network is utilized to optimize an anti-dazzle glass chemical erosion technological parameter, and the BP neural network has the high mapping capability, so that any nonlinear mapping from input to output can be realized. By utilizing the high mapping capability and generalization capability of the BP neural network to establish a nonlinear relation of the temperature, the time and the transmittance, a parameter optimization problem influenced by complicated factors can be solved.

The invention discloses an aerial photogrammetric system integrated with a non-scanning laser radar and an aerial photogrammetric method. The system comprises the non-scanning laser radar, a CCD (Charge Coupled Device) digital camera, a positioning-orienting POS (Passive Optical Splitter) module and a control-storage module. The method comprises the following steps of carrying out multiple-laser-beam irradiation on a visual field range by the non-scanning laser radar based on a focal plane array, so as to determine the distances of many sampling points in a visual field; meanwhile, by utilizing pose data provided by the positioning-orienting POS module, resolving out the geodetic three-dimensional coordinate of each sampling point as ground control information of subsequent aerial photographic processing; collecting an aerial photogrammetric photo of the same visual field by the CCD digital camera, realizing aerial survey mapping according to the information, which is provided by the laser radar, of a ground control point in quick and low-cost manners. According to the aerial photogrammetric system integrated with the non-scanning laser radar and the aerial photogrammetric method, a conventional field ground control method is replaced by adopting the three-dimensional imaging by the non-scanning laser radar; a charting period can be greatly shortened; the cost is decreased; the mapping capacity of a zone which is severe in geographical environment is improved.

The invention discloses a motion mapping method based on a CyberForce teleoperation mechanical arm, belongs to the technical field of robot teleoperation, and aims to solve the problem that the control mapping effect of a conventional control method for robot astronauts is poor as working spaces of the mechanical arm and human arms are inconsistent. The motion mapping method comprises the steps that a motion space of the mechanical arm is divided into a free moving space and a fine operation space; bulges are utilized to represent an outer contour of a reachable working space in a corresponding space; in a bulge outer contour of the free moving space, the position is controlled through set zoom factor mapping and the posture is controlled through posture adjustment mapping according to thereachable working space of the mechanical arm; and in a bulge outer contour of the fine operation space, the position is controlled through variable zoom factor mapping and the posture is controlledthrough posture adjustment mapping according to a set posture space of the mechanical arm. The motion mapping method is used for control of the position and posture of the tail end of the mechanical arm.