Euclidean

The results showed that this method could be used to reconstruct the surgical scene in a close Euclidean space.

But none of the mathematicians believed that these basic non- Euclidean geometries would be physically significant .

However, every attribute has different function in actual samples; the weighted Euclidean distance is usually chosen.

By comparison with retrieving results of Euclidean distance in the same condition, it proved that this method has obvious advantage.

With an Euclidean distance based classifier, each nonoverlapping window of the texture image is then assigned to its corresponding category.

Euclidean norm theory was used to select and optimize the contractors during the evaluation work of the construction projects.

Each position in a 3D space can be represented by such a triple using the Euclidean coordination system for three dimensions.

However, this Euclidean perspective is just one of many possible multi-dimensional varieties of spacetime.

Core 3: The value of Pi is the ratio of any circle's circumference to its diameter in Euclidean space.

It has been proved that this distance measure is more efficient than the Euclidean distance.

The paper introduces the one of non- Euclidean geometry - hyperbolic geometry into special theory of relativity.

The traditional method about KNN is generally used Euclidean distance formula to measure the distance between the two samples.

Economics is not a straightforward discipline like Newtonian mechanics or Euclidean geometry.

The Euclidean distance and weighted methods were considered as the criteria for the Case-Based Reasoning to get the ways of similarity.

The advent of the theory of relativity forced a drastic change in the attitude toward non-Euclidean geometry.

Weighted euclidean distance was used to improve retrieval efficiency.

Science emerged from what was embryonic in the Euclidean demonstrations.

The distance vectors are available in a distance map made by the Euclidean Distance Transform.

One common approximation to the Euclidean Steiner tree problem is to compute the Euclidean minimum spanning tree.

Euclidean distance was used to recognize and analyze unknown samples.

This method established a new kind of relative similarity degree by combining the Euclidean distance with grey correlation degree.

Two- and three-dimensional Euclidean spaces are metric spaces, as are inner product spaces, vector spaces, and certain topological spaces.

It efficiently preserves the global Euclidean distance, i. e. diversity information between data, but fails to the nonlinear data.

but he also studied the calculus of variations, group theory, non-Euclidean geometry, and projective geometry, among other topics.

The essential property and developmental course of Euclidean space, symplectic space and bogus symplectic space are studied.

using the Euclidean distance between the feature to detect objects; Filtering the static object through three continuous frame.

Euclidean quantum gravity does not build in a notion of causality.

symplectic space and Euclidean space are the internal spaces of bogus symplectic space.

Science should always try to use Euclidean geometry and vary the laws of physics where necessary.

Finally, weighted Euclidean distance classifier was utilized in recognition.

In these topological spaces, it usually adopts Euclidean distance to measure similarity between objects.

The global features and local features will be recognized and sorted by weighting Euclidean distance and the minimum distance, respectively.

A new method to deform surfaces using radial basis function is proposed by replacing the Euclidean distance as geodesic distance.

Each innovation destined to dwarf the one extensive accomplishment of the Greeks-Euclidean geometry.

Euclidean geometry is a mathematical system attributed to the Greek mathematician Euclidof Alexandria.

finally, feature points are matched by the Euclidean distance under the continuity constraint.

The iris feature matching was based on the Euclidean distance between the corresponding feature points.

We introduce the Lobachevskian geometry and the Ricmanian geometry by proving the Euclidean of the fifth postulate.

Float vector based image feature has high dimension and usually makes use of Euclidean distance as its similarity definition.

The term " Euclidean" indicates that space and time are treated equally.

The discovery of hyperbolic space ushered in the field of mathematics that is called non-Euclidean geometry.

The non euclidean geometry holds the special status in the history of mathematics.

The Euclidean distance of singular values is used as the measurement of similarity between two gray charts, realizing fault diagnosis.

You all have a sense of what a flat space is, Euclidean space is.

Based on the Euclidean distance, a distributed grid location estimation was proposed as follows to improve the original estimation.

Conventional flow mathematical models of coalbed methane are all based on Euclidean geometry.

In the process of pattern recognition, we use Euclidean distance formula to classify sample.

Section6 includes iris matching via minimum Euclidean distance.

We prefer the form (5. 16. 7) since it is in conformity with the definition of scalar product in a complex Euclidean space.

The result using GTI model is somewhat inferior to Euclidean distance.

then it is isometric to a sphere or an euclidean space or a hyperbolic cylinder.

In addition, it is showed that the conjugate spaces of Weak Euclidean Spaces are still Weak Euclidean Spaces.

Triangle Chess Under Non-Euclidean Space.

Form-Based Code: Solving the ills of Euclidean Zoning?

Hexagon Chess Under Non-Euclidean Space.

Before hyperbolic geometry , mathematicians knew about two kinds of space , Euclidean space and spherical space .

Euclidean geometry LDPC and encoding algorithms based on the parity check matrix are mainly researched. 2.

It's a definition really of Euclidean space.

Those feature vectors are invariant when binary image has been translated, rotated or scaled in 2D Euclidean space R^2.

then it is isometric to an Euclidean space or a hyperbolic cylinder.

However, the conventional RBFs are based on the isotropic Euclidean distance and thus is more applicable to isotropic problems.

In Euclidean geometry, for example, such concepts as "point, " "line, " and "lies on" are usually posited as primitive terms.

Euclidean quantum gravity took a big technical leap during the 1980s and 1990s with the development of powerful computer simulations.

These are Regular Triangles in Non-Euclidean plane.

for example, Euclidean space is invariant under rotations and translations.

Because Euclidean universes have no distinct notion of time, they have no structure to put events into a specific order;

The phenomenal world, that is the world that we experience must, for example, satisfy the exhumes of Euclidean geometry.

Improvement and Implementation of a Polynomial Time Approximation Scheme for Euclidean Traveling Salesman Problem

Generalized normal operator and generalized normal matrix on the general Euclidean space

Janos continued anyway and today is recognized, along with Lobachevsky and Gauss , as one of the discoverers of non-Euclidean geometry;

Hardware Realization of a Fast Algorithm for Euclidean Distance Transformation

On the Isometric Minimal Immersion Into a Euclidean Space

Performance Ratio Analysis of the Convex Hull Method for the Euclidean Traveling Salesman Problem

The least common multiple of several elements in a Euclidean ring

Sub-orthogonal Transformation in Euclidean Spaces and Its Properties

Estimation of smooth empirical euclidean likelihood distribution

Rotational hypersurface about given principal curvature function in euclidean space

solving geometry constraints problems of point - plane configuration in euclidean space

Internal Implication and Expansion of Euclidean Space and Symplectic Space for Bogus Symplectic Space

The Generalization of Metric Equations in the High-Dimensional Euclidean Space and Their Applications

Isometric Transformation and Isometric Mapping in N-dimensional Euclidean Space

Gaussian Intrinsic differential geometry and non-euclidean geometry

The Lagrangian H-umbilical Submanifold in Indefinite Quaternion Euclidean Space Form

The Gradient Extension of a Linear System on Euclidean Space

Two-side pseudo-Euclidean rings and the normal form of matrices on them

On Volume Calculation of Subregion in Euclidean Multidimensional Space

Generalized Metric Equations in Non-Euclidean Space and Their Applications

Definition of Euclidean Correlation Functions

Application of Gradient Method to the Model of Euclidean Metric Location Selection

Fault Diagnosis for Diesel Valve Drain Based on Euclidean Closeness Degree and Frequency Band Energy Decomposition Using Wavelet Packets

A New Technique to Design Polynomial Time Approximation Schemes in Euclidean Space

Applications of the Metric Equations in Non-euclidean space

A Type of Maximal Subgroups of Special Orthogonal Groups over Euclidean Domains

Euclidean and Non- Euclidean Geometry: An analytic approach

A Parallel Algorithm for Quasi Euclidean Distance Transform

Some basic theorems on higher dimensional non-euclidean geometry

A united method for greatest common factor and least common multiple in euclidean ring

Fractals are purely a wonder - too irregular for Euclidean geometry;

Computer and architecture: The process of generation of the Non-Euclidean space

Method of Establishing Duality Principle for Euclidean Plane

Infinity Harmonic Maps Between Semi-Euclidean Spaces

On Some Results of Harmonic Morphisms between Semi-Euclidean Spaces

An Improved Genetic Algorithm to Solve the Euclidean Plane TSP by Using Geometry Structure

Some Metric Problems in Non-Euclidean Elliptic Geometries

Based-on Euclidean Distance Method for Improving the Classification Errors of Artificial Neural Networks

A New Algorithm for Complete Euclidean Distance Transform

Matrix Analysis Method for Some Volume Problems in Euclidean Space Rn

Matteo Ricci and the Introduction of Western Non-Euclidean Geometry

The First Eigenvalue of Space-like Submanifold in Pseudo-euclidean Space

The Symmetric Linear Transformation for Two Euclidean Subspaces

Another prove of spectrum mapping theory in Euclidean space

The Independence of Several Axioms in Euclidean System

Properties of Ruled Surfaces in Pseudo-Euclidean Space

Integrated Dynamic Radio Resource Management Based on Euclidean Distance Metric

Research on Distance from Point in to Hyperplane in Euclidean Space

A New Method of Three-Dimensional Euclidean Distance Transform

A Fast Algorithm for Complete Euclidean Distance Transformation Based on Contour Scanning

Multi-Modal Data Fusion for Person Authentication based on Weighted Euclidean Distance Method

Automatic image mosaic technology based on least Euclidean distance criteria of net template

artificial immune algorithm based on euclidean distance and king - crossover

A Model Based on Euclidean Distance for Performance Evaluation of Camouflage Equipment

The Angles Between Two Space-like Vectors and Between Two Space-like Subspaces in Pseudo-Euclidean Space

Right triangles and Euclidean norms

Study on Algorithm for State Prediction of Rotary Kiln Based on Euclidean Distance and Phase Plane

Modified Polygonal Mesh Voxelization Based on Euclidean Distance Measurement

Surfaces in Euclidean Space with Conformal Gauss MapBaskakov-Durrmeyer

From Relation Space to Euclidean Space

The elements of non-Euclidean geometry

Corner detection algorithm based on euclidean distance

Fast Euclidean Distance Transform Based on Contour Tracking

Calculation of Euclidean Distance between Vertices Based on VCC

Cultural Angle of View of Euclidean Geometry

On equal-distance sets in Euclidean Space En

A topology on the family of some convex subsets in finite dimension Euclidean space

n dimensional euclidean space n

The random covering in Euclidean space and it's application

A principal ideal ring that is not a Euclidean ring

On Some Epistemology Problems in the Development of Non-Euclidean Geometry