IEEE

Robust Fault Classification of Three Phase Induction Motor Using GWO-SVM With Simulation and Hardware Validation

Abstract: This paper presents a comprehensive fault classification framework for three-phase Induction Motors (IMs) using a novel Grey Wolf Optimization-enhanced Support Vector Machine (GWO-SVM) ...
Nature

Hybrid CNN-decision tree framework for efficient transmission line fault detection and classification: an XAI-based approach

Accurate, fast, and interpretable fault identification on electrical transmission lines is essential for maintaining power system stability and reducing outage durations. In this study, we propose a ...
GitHub

Euclidean and Mutual Reachability Minimum Spanning Trees

Euclidean Minimum Spanning Trees using single-, sesqui-, and dual-tree Borůvka algorithms, which are quite fast in spaces of low intrinsic dimensionality, minimum spanning trees with respect to mutual ...
Nature

A novel hybrid inception-xception convolutional neural network for efficient plant disease classification and detection

Plants are essential at all stages of living things. Plant pests, diseases, and symptoms are most regularly visible in plant leaves and fruits and sometimes within the roots. Yet, their diagnosis by ...
LinkedIn

MATLAB and its applications in Data Science and Machine Learning

MATLAB is one of the most widely utilized computational software platforms. The initial version was developed in the late 1970s by Cleve Moler, the chairman of the computer science department at the ...
Frontiers

Reproducible supervised learning-assisted classification of spontaneous synaptic waveforms with Eventer

Detection and analysis of spontaneous synaptic events is an extremely common task in many neuroscience research labs. Various algorithms and tools have been developed over the years to improve the ...
GitHub

Case Drone signature classification

Extract characteristic features for every UAV, distinguishing it from the others. Use the features to classify (through multi-class model) to determine the type of UAV. Use the features to determine ...
IEEE

Hardware Design of Lightweight Binary Classification Algorithms for Small-Size Images on FPGA

Abstract: This study explores the implementation of lightweight binary classification algorithms on low-cost Field-Programmable Gate Arrays (FPGAs) for medical image analysis. Recognizing the growing ...
Scientific Research Publishing

A Novel Efficient and Effective Preprocessing Algorithm for Text Classification ()

1 College of Information Science and Technology, Jinan University, Guangzhou, China. 2 University of Birmingham Joint Institute, Jinan University, Guangzhou, China. Text classification is an essential ...
snmjournals.org

A Comparison of Random Forest and K-Means Clustering Algorithms for Classification of 18F-Florbetapir PET

Introduction: We compare the use of two machine learning (ML) algorithms: random forests (RFs) and k-means clustering (KMC), for classification of presence or absence of amyloid deposition using 18 ...
Frontiers

Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy

Intrinsically disordered proteins lack a stable tertiary structure and form dynamic conformational ensembles due to their characteristic physicochemical properties and amino acid composition. They are ...