High Speed Sphere Machines
A sphere machine creates a perfect rounded ball of rock or glass. The High Speed Sphere Machine was engineered to be a high-performing and high-precision machine that allows a lapidarist to produce a well-polished sphere in less than an hour. The framework is designed to be a heavy-duty base for the machine, partnered
Energies | Free Full-Text | Fault Detection and Classification …
Integrating inverter-based generators in power systems introduces several challenges to conventional protection relays. The fault characteristics of these generators depend on the inverters' control strategy, which matters in the detection and classification of the fault. This paper presents a comprehensive machine-learning-based approach for …
Plotz
Create perfect hollow spheres using Plotz, the HTML5 modeller for Minecraft. Plotz can model spheres up to 256 blocks diameter. If you are building a sphere using Plotz, this …
A Randomized Sphere Cover Classifier | SpringerLink
This paper describes an instance based classifier, the randomised sphere covering classifier (αRSC), that reduces the training data set size without loss of accuracy when compared to nearest neighbour classifiers.The motivation for developing this algorithm is the desire to have a non-deterministic, fast, instance based classifier that performs well …
Generating Meshes of a Sphere
Generating an icosphere basically requires three steps: Generate an initial icosahedron. Subdivide the triangles. Project the vertices to the sphere. I already …
Generator Born from Classifier
The majority of machine learning research bifurcates into two distinct branches of study: the predictive task and the generative task. Given the input x and the label y, the former one focuses on the training ... trained classifier or directly solving this inverse problem from classifier to generator poses significant challenges. Despite these ...
Air Classifier
Air Classifier. According to the centrifugal force, gravity, inertial force, etc. of particles of different sizes in the medium (usually air), different trajectories are generated, so as to …
Sphere Machines
Covington Engineering lapidary sphere machines, choose between 3 models. The three headed sphere machine is designed specifically for lapdiary use.
Hyper-Sphere Support Vector Classifier with Hybrid Decision …
Based on detailed analysis of relationships between bounding hyper-spheres, a hybrid decision strategy is put forward to solve classification problem of the …
Steel surface defect classification using multiple hyper-spheres
Originated from binary twin hyper-spheres support vector machine, MHSVM+ uses hyper-sphere to solve classification decision problem. Differently, MHSVM+ is a multi-class classifier, where it builds a corresponding hyper-sphere for …
Variational quantum support vector machine based on …
A support vector machine (SVM) is a computer algorithm that learns by examples to assign labels to objects. It is a typical method to solve a binary …
A novel air-suction classifier for fresh sphere fruits in …
To improve the harvesting efficiency of the sphere fruits and reduce the workload of post-harvest classification, an air-suction sphere fruit classifier was designed in this paper, which can achieve the separation of high-quality fruit and common fruit through a pneumatic device according to the size and quality of the fruit when the cones …
A general maximal margin hyper-sphere SVM for multi-class
The classical SVM and M 3 HS-SVM classifiers differ in that the classical SVM classifier is determined by the hyper-plane for binary classification problems, whereas our M 3 HS-SVM classifier is determined by the hyper-sphere for multi-class classification problems. M 3 HS-SVM, in particular, is a general hyper-sphere SVM classifier. These ...
How to Develop an Auxiliary Classifier GAN (AC-GAN) …
The auxiliary classifier GAN is a type of conditional GAN that requires that the discriminator predict the class label of a given image. How to develop generator, discriminator, and composite models for the AC-GAN. How to train, evaluate, and use an AC-GAN to generate photographs of clothing from the Fashion-MNIST dataset.
An efficient randomised sphere cover classifier
An efficient randomised sphere cover classifier (αRSC), that reduces the training data set size without loss of accuracy when compared to nearest neighbour classifiers, is described. This paper describes an efficient randomised sphere cover classifier (αRSC), that reduces the training data set size without loss of accuracy when compared to …
Support vector machine with quantile hyper-spheres for …
These classifiers include maximal-margin spherical-structured multi-class SVM (MSM-SVM) [20], twin support vector hyper-sphere (TSVH) [21], twin-hypersphere support vector machine (THSVM) [22], maximum margin and minimum vol-ume hyper-spheres machine with pinball loss (Pin-M3HM) [23] and least squares twin support vector hyper-sphere …
Free Citation Generator | APA, MLA, Chicago | Scribbr
Generate citations in APA, MLA, Chicago, and Harvard style with Scribbr's free Citation Generator. Trusted by students worldwide.
Support vector machine with quantile hyper-spheres for …
This paper formulates a support vector machine with quantile hyper-spheres (QHSVM) for pattern classification. The idea of QHSVM is to build two quantile hyper-spheres with the same center for positive or negative training samples.
A twin hyper-sphere multi-class classification support vector machine …
Experimental results on six benchmark datasets indicate that THKSVM yields the comparable prediction accuracy with other algorithms, but it costs the shortest computational time among four algorithms. For the binary classification problem, twin hyper-sphere support vector machine (THSVM) is an improvement on the twin support vector …
Twin pinball loss support vector hyper-sphere classifier for …
From the classification experiments for synthetic and UCI datasets, it can be clearly seen that TPSVH has better classification accuracy and generalization performance compared with other classifiers. Motivated by twin support vector hyper-sphere (TSVH) and support vector machine with pinball loss (pin-SVM), this paper formulated a twin …
A New Weighted Hyper-Sphere Support Vector Machine
A new weighted hyper-sphere SVM based on the analysis of performance influence caused by the class size is presented, which can control the misclassification rate efficiently and improve the generalization of the classifier. Since hyper-sphere SVM treat all samples equally, its performance is lower when distribution of the training examples is uneven.
Sora | OpenAI
Sora is an AI model that can create realistic and imaginative scenes from text instructions.
Universal expressiveness of variational quantum classifiers
Rigorous results about the real computational advantages of quantum machine learning are few. Here, the authors prove that a PROMISEBQP-complete problem can be expressed by variational quantum ...
Spheronizer NEA|Sphere: Neuman & Esser
For special challenges in particle size ratios, such as a particularly narrow d90/d10 ratios, NEUMAN & ESSER has developed the NEA|Sphere C classifier based on the proven GRC guide ring classifier. This unit also allows efficient fractionation of …
How Naive Bayes Algorithm Works? (with example and …
Naive Bayes is a probabilistic machine learning algorithm based on the Bayes Theorem, used in a wide variety of classification tasks. In this post, you will gain a clear and complete understanding of the Naive Bayes algorithm and all necessary concepts so that there is no room for doubts or gap in understanding. Contents 1. … How Naive …
A general maximal margin hyper-sphere SVM for multi-class
In this study, we proposed a maximal margin hyper-sphere SVM for multi-class classification patterns (M 3 HS-SVM). More concretely, only one optimization problem is built to obtain k hyper-sphere classifiers in terms of …
(PDF) A fault detector/classifier for closed-ring power generators …
A fault detector/classifier for closed-ring power generators using machine learning
Building a Multi-class Password Strength Generator and …
Building a Multi-class Password Strength Generator and Classier Model by Augmenting Supervised Machine Learning Techniques Sakya Sarkar Sakya Asansol Institute of Engineering & Management ...
Multi-class classification method for strip steel surface
Focusing on strip steel surface defects classification, a novel support vector machine with adjustable hyper-sphere (AHSVM) is formulated. Meanwhile, a new multi-class classification method is proposed. Originated from support vector data description, AHSVM adopts hyper-sphere to solve classification problem. AHSVM can obey two …
Support vector machine with quantile hyper-spheres for …
This paper formulates a support vector machine with quantile hyper-spheres (QHSVM) for pattern classification. The idea of QHSVM is to build two quantile hyper-spheres with the same center for positive or negative training samples. Every quantile hyper-sphere is constructed by using pinball loss instead of hinge loss, which …