Plane Parameters(平面参数)研究综述
Plane Parameters 平面参数 - Similar phase behavior is observed when examining the in-plane parameters. [1] Therefore, the purpose of this paper is to develop a model based on the least square adjustment and focus on the weight of the plane parameters which created by a robust least square fitting algorithm. [2] We determine the trajectory of the UAS by combining the laser scanner measurements with the plane parameters. [3] The hyperplane parameters of TwinSVM are optimized using Genetic algorithm (GA). [4] A cubical function is considered for the in-plane parameters as a combination of a linear zigzag function with different slopes at each layer over the entire thickness while a quadratic function is assumed for the out-of-plane parameters of the core and constant in the face sheets. [5] Then, the planar primitives are generated by clustering these regions into some distinct groups according to their plane parameters. [6] PlaneRCNN employs a variant of Mask R-CNN to detect planes with their plane parameters and segmentation masks. [7] The proposed heuristic algorithm-based filtering method is compared with the singular value decomposition method, which is frequently used in literature to obtain the plane parameters. [8] In this case four in-plane parameters of orthotropic composite material were determined using finite element updating method as a solution for the inverse problem, digital image correlation for full-field measurement and Gauss-Newton algorithm as an optimization procedure. [9] By introducing the B-plane parameters, the initial states determination under the constraint of the gravity assist is developed. [10] Radiological evaluation of femoroacetabular impingement is based on single-plane parameters such as the alpha angle or the center edge angle, or complex software reconstruction. [11]在检查面内参数时观察到类似的相位行为。 [1] 因此，本文的目的是开发一个基于最小二乘平差的模型，重点关注由稳健的最小二乘拟合算法创建的平面参数的权重。 [2] 我们通过将激光扫描仪测量值与平面参数相结合来确定 UAS 的轨迹。 [3] TwinSVM 的超平面参数使用遗传算法 (GA) 进行优化。 [4] 面内参数考虑三次函数，作为在整个厚度上每层具有不同斜率的线性之字形函数的组合，而二次函数假设核心的面外参数和常数面片。 [5] 然后，通过根据平面参数将这些区域聚类成一些不同的组来生成平面图元。 [6] PlaneRCNN 使用 Mask R-CNN 的变体来检测带有平面参数和分割掩码的平面。 [7] 将所提出的基于启发式算法的滤波方法与文献中常用的奇异值分解方法进行比较，以获得平面参数。 [8] 在这种情况下，正交异性复合材料的四个面内参数被确定为使用有限元更新方法作为反问题的解决方案，用于全场测量的数字图像相关性和作为优化程序的高斯-牛顿算法。 [9] 通过引入B平面参数，发展了重力辅助约束下的初始状态确定。 [10] 股骨髋臼撞击的放射学评估基于单平面参数，例如 α 角或中心边缘角，或复杂的软件重建。 [11]
3d Plane Parameters 3d 平面参数
Recent approaches for single-view reconstruction employ multi-branch neural networks to simultaneously segment planes and recover 3D plane parameters. [1] Recent studies on planar scene modeling from a single image employ multi-branch neural networks to simultaneously segment pla-nes and recover 3D plane parameters. [2] Single-image piece-wise planar 3D reconstruction aims to simultaneously segment plane instances and recover 3D plane parameters from an image. [3]最近的单视图重建方法采用多分支神经网络来同时分割平面并恢复 3D 平面参数。 [1] 最近对单个图像的平面场景建模的研究采用多分支神经网络来同时分割平面并恢复 3D 平面参数。 [2] 单图像分段平面 3D 重建旨在同时分割平面实例并从图像中恢复 3D 平面参数。 [3]
Sagittal Plane Parameters 矢状面参数
METHODS Baseline, 6-week, 6-month, 1-year and 2-year follow-up radiographs were analyzed for sagittal plane parameters (LL, PI, PT and TL kyphosis). [1] Furthermore, non-sagittal plane parameters have mostly not been considered, whereby the evaluation of e. [2]方法 基线、6 周、6 个月、1 年和 2 年的随访 X 线片分析矢状面参数（LL、PI、PT 和 TL 后凸）。 [1] 此外，非矢状面参数大多没有被考虑，从而评估 e。 [2]