Results 61 to 70 of about 52,299 (258)

Unveiling the Potential of Local Outlier Factor in Credit Card Fraud Detection

International Journal of Informatics, Information System and Computer Engineering
This study evaluates the Local Outlier Factor (LOF) algorithm for credit card fraud detection, emphasizing its effectiveness with highly imbalanced datasets.
Angel Jones, Marwan Omar
doaj   +1 more source

An Improved Forward-Looking Sonar 3D Visualization Scheme of Underwater Objects

IEEE Access, 2019
This paper presents an improved scheme for forward-looking sonar (FLS) visualization, including an echo acquisition method, a global threshold based on local outlier factor and a reconstruction method.
Teng Zeng, Chunhua Zhang, Yong Huang, Peng Wang   +3 more
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model

Sensors, 2016
In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle (UAV) applications, e.g., autonomous tracking and chasing a moving ...
Changhong Fu, Ran Duan, Dogan Kircali, Erdal Kayacan   +3 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Application of Local Outlier Factor Algorithm to Detect Anomalies in Computer Network

Elektronika ir Elektrotechnika, 2018
Gap between the new attack appearance and signature creation for this attack may be critical. During this time, many computer systems may be affected and valuable resources may be lost. Even after signature creation, many computer systems still stay vulnerable because of bad security practice, i.e.
Auškalnis, Juozas, Paulauskas, Nerijus, Baškys, Algirdas   +2 more
openaire   +3 more sources

Influence of TiC and TiN Ceramic Reinforcements on the Microstructure, Thermal Expansion Behavior, and Tensile Properties of Invar 36 Manufactured by Laser Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji, Natasha Sacks, Johannes Pötschke, Björn Matthey   +3 more
wiley   +1 more source

Power Prediction of Photovoltaic Power Generation Based on Improved Gaussian Process Regression Modeling

Taiyuan Ligong Daxue xuebao
Purposes The proportion of photovoltaic(PV) power generation has been increasing in China. PV power generation is greatly affected by meteorological factors and its output power shows strong intermittency and volatility because of the complexity and ...
XIAO Chun, HAO Junbo, YANG Xiaoxia, HAN Xiaoqing   +3 more
doaj   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Automatic Detection of Age-Related Macular Degeneration Based on Deep Learning and Local Outlier Factor Algorithm. [PDF]

Diagnostics (Basel), 2022
He T, Zhou Q, Zou Y.
europepmc   +1 more source