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5 results about "Error surface" patented technology

An intelligent detection method and system for subgrade filling compaction degree

The application relates to the technical field of road engineering quality detection, and discloses a subgrade filling compaction degree intelligent detection method and system, which comprises the following steps: a multispectral remote sensing subsystem is controlled to collect images and generate orthographic images, and initial compaction degrees are calculated after interference masks are removed by vegetation and water body indexes; data heterogeneity and spectral characteristics are analyzed to generate sampling instructions containing suggestion coordinates; measured values fed back by a dynamic sampling subsystem are acquired, residual error vectors are calculated, and residual error correction surfaces covering the whole field are constructed; initial data and residual error surfaces are weighted and superimposed by using a dynamic correction coefficient to generate a final compaction degree distribution map. Through the combination of a multivariate regression model and a ground measured residual error correction mechanism, an adaptive sampling strategy based on spatial heterogeneity is used to guide accurate detection, the problems that a single remote sensing inversion is greatly disturbed by the environment and traditional sampling is insufficient in representativeness are effectively solved, and the comprehensiveness and accuracy of subgrade compaction degree detection are improved.
Owner:PING AN INSPECTION TECH (SHANDONG) GRP CO LTD

A Mesh Reconstruction Method and System Based on 3D Gaussian Scatter Points

PendingCN122312960AGraphicsAlgorithm
This invention relates to the interdisciplinary field of computer vision and graphics. It provides a method and system for mesh reconstruction based on 3D Gaussian scattering. The method includes obtaining a 3D Gaussian sputtering representation of a target scene, constructing an initial triangular mesh, selecting triangular faces from the initial triangular mesh to form a high-confidence seed face set, performing iterative region growth to reconstruct the surface mesh, stopping growth when no new candidate triangular faces are accepted or the iteration termination condition is met, and performing topological correction and smoothing on the final surface mesh to output the reconstructed 3D mesh model. By employing a strategy of "high-confidence seed selection" and "multi-criteria iterative growth," the reconstruction is ensured to start from a reliable geometric region, and newly added faces are strictly constrained to maintain smooth continuity with the already reconstructed parts in terms of geometry, scale, and appearance. This avoids the spread of erroneous faces and enables the reconstruction of a mesh model with rich details and strong visual consistency.
Owner:WUYI UNIV

Error surface based sub-pixel accurate refinement method for decoder side motion vector refinement

PendingUS20260046439A1Digital video signal modificationCost evaluationMotion vector
Given that decoder side motion vector refinement / derivation is a normative aspect of a coding system, the encoder will also have to perform the same error surface technique in order to not have any drift between the encoder's reconstruction and the decoder's reconstruction. Hence, all aspects of all embodiments are applicable to both encoding and decoding systems. In template matching, the refinement movement occurs only in the reference starting from the sub-pixel accurate center that is derived based on the explicitly signaled merge index or implicitly through cost evaluations. In bilateral matching (with or without averaged template), the refinements start in the reference lists L0 and L1 starting from the respective sub-pixel accurate centers that are derived based on the explicitly signaled merge index or implicitly through cost evaluations.
Owner:HUAWEI TECH CO LTD

Physical digital twin modeling method and apparatus for assembly, electronic device and medium

The embodiments of the present disclosure provide a physical digital twin modeling method and apparatus for an assembly, an electronic device and a medium. The physical digital twin modeling method for the assembly includes: generating a geometric distribution error surface of an assembly surface of a part; establishing an ideal model of the part without the geometric distribution error surface; integrating the geometric distribution error surface with the ideal model to establish a geometric distribution error integrated model of the part; assembling the geometric distribution error integrated model on a computer to establish a geometric digital twin model; and adding physical conditions to the geometric digital twin model of the assembly to establish a physical digital twin model of the assembly.
Owner:BEIJING INST OF TECH

A multi-agent system cooperative control method supporting unknown direction drive fault

The application discloses a kind of unknown direction drive fault supported multi-agent system cooperative control method, it is related to multi-agent cooperative control field.Firstly, the MIMO multi-agent dynamics model containing unknown control gain is established, and the positive definiteness restriction to control gain matrix is relaxed by matrix decomposition technique;Second, a unified drive fault model is constructed, covering reverse fault, performance loss and overload and other complex working conditions;Then introduce local neighbor auxiliary compensation variable and error surface, construct Lyapunov function;On this basis, design adaptive fault-tolerant cooperative control protocol based on series Nussbaum function, effectively deal with unknown and inconsistent multiple control directions;Finally, drive reverse experiment is verified through multi-mobile robot platform.The application can ensure that multi-agent system asymptotically reaches consensus under the condition that drive direction is completely unknown or even reversed, significantly improve the fault tolerance and operation safety of the system under extreme fault conditions.
Owner:GUIZHOU UNIV +1