Results 101 to 110 of about 49,315 (263)

Comparative Evaluation of Nonparametric Density Estimators for Gaussian Mixture Models with Clustering Support

Axioms
The article investigates the accuracy of nonparametric univariate density estimation methods applied to various Gaussian mixture models. A comprehensive comparative analysis is performed for four popular estimation approaches: adaptive kernel density ...
Tomas Ruzgas, Gintaras Stankevičius, Birutė Narijauskaitė, Jurgita Arnastauskaitė Zencevičienė   +3 more
doaj   +1 more source

Ultrasound Entropy Imaging Based on the Kernel Density Estimation: A New Approach to Hepatic Steatosis Characterization. [PDF]

Diagnostics (Basel), 2023
Gao R, Tsui PH, Wu S, Tai DI, Bin G, Zhou Z.   +5 more
europepmc   +1 more source

Kernel Density Estimated Linear Regression

The International FLAIRS Conference Proceedings
Regression analysis is a cornerstone of predictive modeling, with linear regression and kernel regression standing as two of its most prominent paradigms. However, each approach has inherent limitations: linear regression is highly susceptible to outliers in noisy and unevenly distributed datasets, while kernel regression often suffers from overfitting.
Roshan Kalpavruksha, Rohan Kalpavruksha, Teryn Cha, Sung-Hyuk Cha   +3 more
openaire   +2 more sources

Flexible Sensors for Robotics Tactile Perception: A Review

Advanced Robotics Research, EarlyView.
Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Temporal adaptive kernel density estimation for short-term uncertainty modeling of renewable energy generation

International Journal of Electrical Power & Energy Systems
Kernel density estimation (KDE) is widely employed to analyze the short-term uncertainty associated with renewable energy generation in power systems, owing to its ability to estimate probability density functions without prior distribution assumptions ...
Xiao Yang, Tian-Tian Yu, Shichang Cui, Guokai Hao, Fei Hu   +4 more
doaj   +1 more source

NeuroSuite for Long‐Term Functional and Structural Studies of Air‐Liquid Interface Cerebral Organoids

Advanced Science, EarlyView.
NeuroSuite provides a modular hardware‐software platform integrating Neuroweb and NeuroMaps to enable long‐term, in situ electrophysiological interrogation of air–liquid interface organoid slices while preserving tissue architecture. Its components can be used together or independently to capture real‐time activity, spatial network dynamics, and ...
Belquis Haider, Sagnik Middya, Daniel J. Lloyd‐Davies‐Sánchez, Nino F. Läubli, Sulay Vora, Jakob Träuble, Rohan N. Krajeski, Yuqing Feng, Daniel Duncko, Josiah S. Riley, Rubén Ruiz‐Mateos Serrano, Ole Paulsen, Madeline A. Lancaster, George G. Malliaras, Gabriele S. Kaminski Schierle   +14 more
wiley   +1 more source

Uncertainty-Aware State of Energy Estimation for Lithium-Ion Batteries via Hybrid Kernel Sparse Gaussian Process

Batteries
This work develops a hybrid kernel sparse Gaussian process regression integrated with kernel density estimation (HCSGPR-UQ) to resolve three critical drawbacks of conventional lithium-ion battery State of Energy (SOE) estimators: degraded accuracy under ...
Chaoyu Xiao, Haotian Shi, Lei Chen, Zhijun Cai, Yuanru Zou, Chunmei Yu   +5 more
doaj   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Support vector data description with kernel density estimation (SVDD-KDE) control chart for network intrusion monitoring. [PDF]

Sci Rep, 2023
Ahsan M, Khusna H, Wibawati, Lee MH.
europepmc   +1 more source