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3D modeling software component
A geometric modeling kernel is a solid modeling software component used in computer-aided design (CAD) packages. Available modelling kernels include: ACIS
Geometric_modeling_kernel
Geometric modeling is a branch of applied mathematics and computational geometry that studies methods and algorithms for the mathematical description of
Geometric_modeling
Geometric modelling kernel
engineering Geometric modeling kernel Geometric modeling Solid modeling Boundary representation "Adventures in developing a cross-platform kernel". c3dlabs
C3D_Toolkit
Geometric modeling kernel
Russian Geometric Kernel (also known as RGK) is a proprietary geometric modeling kernel developed by several Russian software companies, most notably
Russian_Geometric_Kernel
3D computer graphics software
computer graphics software program that runs on the Parasolid geometric modeling kernel. The Software supports Windows, MacOS, and Linux - namely Debian
Plasticity_(software)
Computer-aided design software
open-source Open Cascade Technology geometric modeling kernel to the industry-leading Parasolid geometry kernel, enhancing modeling precision and compatibility
Shapr3D
Digital Geometric Kernel (former KernelCAD) is a software development framework and a set of components for enabling 3D computer graphics computer-aided
Digital_Geometric_Kernel
Geometric modeling kernel developed by Spatial Corporation
The 3D ACIS Modeler (ACIS) is a geometric modeling kernel developed by Spatial Corporation (formerly Spatial Technology), part of Dassault Systèmes. ACIS
ACIS
Geometric modeling kernel
Parasolid is a geometric modeling kernel originally developed by Shape Data Limited, now owned and developed by Siemens Digital Industries Software. It
Parasolid
Software to use their software as a Computer-aided manufacturing Geometric modeling kernel within their system. In June 2002 they bought the machining STRATEGIST
NC_Graphics
Software for 3D computer-aided design
released by Intergraph in 1996, using the ACIS geometric modeling kernel, it changed to using the Parasolid kernel when it was purchased and further developed
Solid_Edge
Set of principles for modeling solid geometry
(solids). Solid modeling is distinguished within the broader related areas of geometric modeling and computer graphics, such as 3D modeling, by its emphasis
Solid_modeling
Constraint programming setting
Unity3D contains simple geometric constraint solver. Geometric modeling kernel Roller, edited by Beat Brüderlin, Dieter (1998). Geometric Constraint Solving
Geometric_constraint_solving
Topics referred to by the same term
Surface, a library of algorithms for handling surface meshes; see Geometric modeling kernel Global Telecommunications System, a global network for the transmission
GTS
3D modeling kernel developed by Autodesk
Autodesk ShapeManager is a 3D geometric modeling kernel used by Autodesk Inventor and other Autodesk products that is developed inside the company. It
ShapeManager
Computer-aided design software
was removed from the Linux version. NX uses Parasolid for its geometric modeling kernel and D-Cubed as associative engine for sketcher and assembly constraints
Siemens_NX
UK software company
licensed geometric modelling kernel in the world. Parasolid, alongside ACIS, is the current industry standard for three-dimensional solid modelling kernel software
Shape_Data
List of notable software written in or for the C++ programming language
designed to provide access to modern Windows APIs. C3D Toolkit — geometric modeling kernel Caffe — deep learning framework CAPD — library for rigorous numerics
List of C++ software and tools
List_of_C++_software_and_tools
Rounding of an interior or exterior corner
appear on welded, soldered, or brazed joints. Depending on a geometric modelling kernel different CAD software products may provide different fillet functionality
Fillet_(mechanics)
Method of representing a 3D object by defining the limits of its volume
surface model constructed by planar surfaces only Bézier curve Bézier surface Combinatorial maps Coons surface Function representation Geometric modeling kernel
Boundary_representation
Way to visualize and design structures
Research in Asia Building information modeling Comparison of CAD software Computer-aided design Geometric modeling kernel Design computing Digital morphogenesis
Computer-aided architectural design
Computer-aided_architectural_design
American 3D graphics software company
abilities. NLib – an advanced geometric modeling kernel based on NURBS curves and surfaces. VSLib – deformable modeling using the constrained optimization
Solid_Modeling_Solutions
3D mechanical CAD design software
software, Fusion. Inventor uses ShapeManager, Autodesk's proprietary geometric modeling kernel. The software can be licensed as a subscription or through pre-paid
Autodesk_Inventor
Concept in statistics
In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method
Kernel_density_estimation
Optimized math routines developed by Intel
Intel oneAPI Math Kernel Library (Intel oneMKL), formerly known as Intel Math Kernel Library, is a library of optimized math routines for science, engineering
Math_Kernel_Library
Topics referred to by the same term
flowering plants ACIS (Alan, Charles, Ian's System), a solid modelling geometric modeling kernel that several CAD packages use Advanced CCD Imaging Spectrometer
Acis_(disambiguation)
American software company, 1986–2000
and had one main product: ACIS, the first commercially available 3D modeling kernel. Through subsequent years, Spatial added products to its portfolio
Spatial_Corp
Computer-aided design software
develop, based in the OPENNURBS Kernel, the 3D CAD Application called Rhinoceros 3D. An independent geometric modeling kernel has been evolving in Russia
History_of_CAD_software
Open-source geometric modelling kernel
The library covers the following topics: Geometry kernels - basic geometric operations on geometric primitives Arithmetic and algebra Convex hull algorithms
CGAL
Method of CAD drawing file translation
protocols, AP 203 and AP 214. Parasolid XT Part of the Parasolid geometric modeling kernel originally developed by Shape Data and currently owned by Siemens
CAD_data_exchange
Category of regression analysis
of non-parametric models for regression. nearest neighbor smoothing (see also k-nearest neighbors algorithm) regression trees kernel regression local regression
Nonparametric_regression
Finite element framework software
with an extensive library of kernels providing residual terms for solid mechanics, Navier–Stokes equations, phase-field models and more. MOOSE uses VTK for
MOOSE_(software)
Set of methods for supervised statistical learning
using the kernel trick, representing the data only through a set of pairwise similarity comparisons between the original data points using a kernel function
Support_vector_machine
Type of feedforward neural network
type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep learning network has been applied to process
Convolutional_neural_network
Constructing product by means of computer
parametric modeler is able to make changes to the part while maintaining geometric and functional relationships. Direct or explicit modeling provide the
Computer-aided_design
eigenfunctions) of the Laplace–Beltrami operator to compare and analyze geometric shapes. Since the spectrum of the Laplace–Beltrami operator is invariant
Spectral_shape_analysis
Continuous stochastic process
A geometric Brownian motion (GBM), also known as an exponential Brownian motion, is a continuous-time stochastic process in which the logarithm of the
Geometric_Brownian_motion
Estimate of an unobservable underlying probability density function
distribution Kernel density estimation Mean integrated squared error Histogram Multivariate kernel density estimation Spectral density estimation Kernel embedding
Density_estimation
A heat kernel signature (HKS) is a feature descriptor for use in deformable shape analysis and belongs to the group of spectral shape analysis methods
Heat_kernel_signature
Parametric CAD software application
application for 2D design, drafting, and 3D solid modeling based on commercial Parasolid geometric kernel. It's primarily developed and distributed by Russian
T-FLEX_CAD
Research field in deep learning
neighborhood notion. Edges however, limited in their modeling capacity as they can only be used to model binary relations among entities of S since every
Topological_deep_learning
Chinese-American mathematician (born 1949)
major contributors to the development of modern differential geometry and geometric analysis. The impact of Yau's work are also seen in the mathematical and
Shing-Tung_Yau
Process of reducing the number of random variables under consideration
graph-based kernel for Kernel PCA. More recently, techniques have been proposed that, instead of defining a fixed kernel, try to learn the kernel using semidefinite
Dimensionality_reduction
Vectorizing features using a hash function
learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features, i.e.
Feature_hashing
3D and 2D computer-aided-design software
using solid modeling technology. IRONCAD uses both Parasolid and ACIS modeling kernels to provide computational methods for solving geometric calculations
IRONCAD
Computer vision framework
surfaces and implicit models including geometric deformable models. In the case of parametric deformable models, the GVF vector field v {\displaystyle
Gradient_vector_flow
C-matrix Events) is a NASA ancillary information system used to compute geometric information used in planning and analyzing science observations obtained
SPICE (observation geometry system)
SPICE_(observation_geometry_system)
Software used in mathematical applications
Mathematical software is software used to model, analyze or calculate numeric, symbolic or geometric data. Numerical analysis and symbolic computation
Mathematical_software
Overview of and topical guide to statistics
Lasso (statistics) Survival analysis Density estimation Kernel density estimation Multivariate kernel density estimation Time series Time series analysis
Outline_of_statistics
Random set of points on a space with random number and random position
{S}}} is its Borel σ-algebra. Consider now an integer-valued locally finite kernel ξ {\displaystyle \xi } from ( Ω , F ) {\displaystyle (\Omega ,{\mathcal
Point_process
Branch of mathematics
because it allows modeling many natural phenomena, and computing efficiently with such models. For nonlinear systems, which cannot be modeled with linear algebra
Linear_algebra
Model in seismic tomography
of the studies that compared both the Born-Fréchet kernel theory and the infinitesimal geometrical ray theory when they used the same datasets to see
Banana_Doughnut_theory
Technique combining machine learning and computer vision
Geometric feature learning is a technique combining machine learning and computer vision to solve visual tasks. The main goal of this method is to find
Geometric_feature_learning
Distance from a data point to a decision boundary
functional margin, defined in terms of the classifier's output, and the geometric margin, defined in terms of distance from the decision boundary. The precise
Margin_(machine_learning)
Projection of data onto lower-dimensional manifolds
Eigenmaps, LLE) as special cases of kernel PCA by constructing a data-dependent kernel matrix. KPCA has an internal model, so it can be used to map points
Nonlinear dimensionality reduction
Nonlinear_dimensionality_reduction
Free and open-source 3D CAD software
general-purpose parametric 3D computer-aided design (CAD) modeler and a building information modeling (BIM) software application with finite element method
FreeCAD
Geometric distribution Geometric median Geometric standard deviation Geometric stable distribution Geospatial predictive modeling Geostatistics German tank
List_of_statistics_articles
Generalized function whose value is zero everywhere except at zero
represented by integration against a kernel K z ( ζ ) {\displaystyle K_{z}(\zeta )} , the Bergman kernel. This kernel is the analog of the delta function
Dirac_delta_function
Type of geometry
geometry with kernel K, then (G/K, H/K) is an effective Klein geometry canonically associated to (G, H). A Klein geometry (G, H) is geometrically oriented
Klein_geometry
3D computer graphics software
variety of geometric primitives, including polygon meshes, Bézier curves, NURBS surfaces, metaballs, icospheres, text, and an n-gon modeling system called
Blender_(software)
Difference between the dimensions of mathematical object and a sub-object
In mathematics, codimension is a basic geometric idea that applies to subspaces in vector spaces, to submanifolds in manifolds, and suitable subsets of
Codimension
American mathematician (1943–2024)
Mathematics at Columbia University. Hamilton is known for contributions to geometric analysis and partial differential equations, and particularly for developing
Richard_S._Hamilton
Mathematical construction used in homotopy theory
to a "nice" topological space, known as its geometric realization. This realization consists of geometric simplices, glued together according to the rules
Simplicial_set
Scientific application
of space, smooth Gaussian-based dielectric distribution function, modeling geometric objects and charge distributions, and treating systems containing
DelPhi
Statistical concept
with other analytic or geometric tools (e.g., phase transitions over diffusive boundaries), such spatially regularized mixture models could lead to more realistic
Mixture_model
The point distribution model is a model for representing the mean geometry of a shape and some statistical modes of geometric variation inferred from a
Point_distribution_model
Geospatial and graph component of Oracle Database
database. (The spatial component of a spatial feature consists of the geometric representation of its shape in some coordinate space — referred to as
Oracle_Spatial_and_Graph
Class of artificial neural networks
Geometric (PyTorch), TensorFlow GNN (TensorFlow), Deep Graph Library (framework agnostic), jraph (Google JAX), and GraphNeuralNetworks.jl/GeometricFlux
Graph_neural_network
N O P Q R S T U V W X Y Z 2D computer graphics 2D geometric model 3D computer graphics 3D modeling 3D projection 3D rendering A-buffer Algorithmic art
List of computer graphics and descriptive geometry topics
List_of_computer_graphics_and_descriptive_geometry_topics
Geometric algorithm
a kernel function of the two points: k : X × X → R {\displaystyle k:X\times X\rightarrow \mathbb {R} } . For example, the popular Gaussian kernel: k
Diffusion_map
Statistical model used in machine learning
models have been applied on a variety of modeling tasks, including: Audio generation Image generation Molecular graph generation Point-cloud modeling
Flow-based_generative_model
Method of plotting numeric data
a box plot, but has enhanced information with the addition of a rotated kernel density plot on each side. The violin plot was proposed in 1997 by Jerry
Violin_plot
Non-Euclidean geometry
hyperbolic space, which is a far-reaching notion including differential-geometric as well as more combinatorial spaces via a synthetic approach to negative
Hyperbolic_space
Computer-aided design software
(based upon ICAD project) ICAD Surfacing Project—Switlik, J.M. Geometric/Knowledge Modeling Challenges Research group that used to work with ICAD: Systems
ICAD_(software)
Method of defining complex surfaces in computer graphics
T-spline kernel Xiao, Wenlei; Liu, Yazui; Li, Rui; Wang, Wei; Zheng, Jianmin; Zhao, Gang (2016-10-01). "Reconsideration of T-spline data models and their
T-spline
Concept in machine learning
that less complex models are expected to generalize better under a Solomonoff prior. Grokking (machine learning) Neural tangent kernel Rocks, Jason W. (2022)
Double_descent
Computer-aided design program
Album Views. It is part-compatible with Pro/ENGINEER, and uses the Granite kernel, but otherwise is a freestanding CAD system. Initially written by David
Pro/DESKTOP
Non-local formulation of continuum mechanics
Emma; Linder, Christian (August 2017). "Modeling tumor growth with peridynamics". Biomechanics and Modeling in Mechanobiology. 16 (4): 1141–1157. doi:10
Peridynamics
outliers and using a kernel-weighted sampling method to estimate the probability density distribution. For regression-based QSAR models, a widely used technique
Applicability_domain
Probabilistic model
graphical models include causal inference, information extraction, speech recognition, computer vision, decoding of low-density parity-check codes, modeling of
Graphical_model
Statistics and machine learning technique
including both regression and classification tasks, can be explained using a geometric framework. Within this framework, the output of each individual classifier
Ensemble_learning
Process of calculating the causal factors that produced a set of observations
known as mathematical modeling and the above-mentioned physical parameters are called the model parameters or simply the model. To be precise, we introduce
Inverse_problem
Mathematical abstraction of objects being "visible"
determination Hidden line removal z-buffering portal engine Star-shaped polygon Kernel of a polygon Isovist Viewshed Zone of Visual Influence Painter's algorithm
Visibility_(geometry)
methodology for data modeling, predictive analytics, dynamical system analysis, machine learning and time series analysis. Mathematical models have tremendous
Empirical_dynamic_modeling
types of manifolds, there are various types of maps of manifolds. In geometric topology, the basic types of maps correspond to various categories of
Maps_of_manifolds
Branch of mathematical analysis
non-singular kernels provide distinct mechanisms for modeling anomalous diffusion. The Atangana–Baleanu–Caputo (ABC) operator, with its Mittag-Leffler kernel, yields
Fractional_calculus
Canadian-American computational biologist
study of cancer. She is particularly known for her research on string kernels for support vector machine classification of biological sequences. She
Christina_S._Leslie
software CAD data exchange CAD/CAM in the footwear industry List of 3D modeling software List of BIM software List of computer-aided engineering software
List_of_CAx_companies
Type of statistical model
So far, partially linear model was optimized in many other statistic methods. In 1988, Robinson applied Nadaraya-Waston kernel estimator to test the nonparametric
Partially_linear_model
Image processing filter that can be rotated to any orientation
making them ideal for creating steerable 3D kernels. Features within the network are treated as geometric tensors, which are mathematical objects (like
Steerable_filter
Concepts from linear algebra
λ {\displaystyle \lambda } (possibly a negative or complex number). Geometrically, vectors are multi-dimensional quantities with magnitude and direction
Eigenvalues_and_eigenvectors
On short connecting nets with added points
approximate kernelization scheme (PSAKS): for any ε > 0 {\displaystyle \varepsilon >0} it is possible to compute a polynomial-sized kernel, which looses
Steiner_tree_problem
Dividing things between two categories
other kernel-based learning methods. Cambridge University Press, 2000. ISBN 0-521-78019-5 ([1] SVM Book) John Shawe-Taylor and Nello Cristianini. Kernel Methods
Binary_classification
Russian mathematician (born 1966)
is known for his contributions to the fields of geometric analysis, Riemannian geometry, and geometric topology. In 2005, Perelman resigned from his research
Grigori_Perelman
Method of data interpolation and smoothing
technique for data interpolation and smoothing. They were introduced to geometric design by Duchon. They are an important special case of a polyharmonic
Thin_plate_spline
Statistical method
(2006). "On robust estimation and smoothing with spatial and tonal kernels". Geometric properties for incomplete data. Berlin, Germany: Springer. Mumford
Step_detection
Method of detecting shapes within images
each cluster, votes are cast using an oriented elliptical-Gaussian kernel that models the uncertainty associated with the best-fitting line with respect
Hough_transform
American mathematician (b. 1949)
Vancouver. His early work included a study of the asymptotics of the Bergman kernel off the boundaries of pseudoconvex domains in C n {\displaystyle \mathbb
Charles_Fefferman
differential operator Dirichlet–Poisson problem Discrete Poisson equation Poisson kernel Poisson integral formula Poisson–Jensen formula Fourier analysis Poisson
List of things named after Siméon Denis Poisson
List_of_things_named_after_Siméon_Denis_Poisson
Mathematical category
S[T] for a geometric theory T, then the universal property says that its points are the models of T (in any stage of definition Y). A geometric morphism
Topos
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL
GEOMETRIC MODELING-KERNEL