Results 61 to 70 of about 185,151 (349)

dropCyclic: Snapshot Ensemble Convolutional Neural Network Based on a New Learning Rate Schedule for Land Use Classification

IEEE Access, 2022
The ensemble learning method is a necessary process that provides robustness and is more accurate than the single model. The snapshot ensemble convolutional neural network (CNN) has been successful and widely used in many domains, such as image ...
Sangdaow Noppitak, Olarik Surinta
doaj   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

Data Complexity in Machine Learning and Novel Classification Algorithms [PDF]

, 2006
This thesis summarizes four of my research projects in machine learning. One of them is on a theoretical challenge of defining and exploring complexity measures for data sets; the others are about new and improved classification algorithms.
Li, Ling
core   +1 more source

A Review of Space Target Recognition Based on Ensemble Learning

Aerospace
The increasing number of space debris and space-active targets makes the space environment more and more complex. Space target recognition, a crucial component of space situational awareness, is of paramount importance to space security.
Shiyan Wang, Danpu Zhao, Haikun Hong, Kexian Sun   +3 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Self-poised Ensemble Learning

, 2005
This paper proposes a new approach to train ensembles of learning machines in a regression context. At each iteration a new learner is added to compensate the error made by the previous learner in the prediction of its training patterns. The algorithm operates directly over values to be predicted by the next machine to retain the ensemble in the target
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga   +3 more
openaire   +3 more sources

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source

Automatic Music Genre Classification Using Ensemble of Classifiers [PDF]

, 2007
This paper presents a novel approach to the task of automatic music genre classification which is based on multiple feature vectors and ensemble of classifiers. Multiple feature vectors are extracted from a single music piece.
Celso A. A. Kaestner, Carlos N. Silla Jr., Alessandro L. Koerich, Silla Jr, Carlos N., Koerich, Alessandro L., Kaestner, Celso A.A.   +5 more
core   +1 more source

A Python code smell detection method based on ensemble learning

上海师范大学学报. 自然科学版
A Python code odor detection method based on ensemble learning was proposed in this paper, which was used to detect five types of code smell. Two ensemble learning methods, stacked ensemble and voting ensemble, were adopted to detect code smell, and ...
CAO Yue, CHEN Junhua
doaj   +1 more source

Learning enhanced ensemble filters

Journal of Computational Physics
The filtering distribution in hidden Markov models evolves according to the law of a mean-field model in state-observation space. The ensemble Kalman filter (EnKF) approximates this mean-field model with an ensemble of interacting particles, employing a Gaussian ansatz for the joint distribution of the state and observation at each observation time ...
Eviatar Bach, Ricardo Baptista, Edoardo Calvello, Bohan Chen, Andrew Stuart   +4 more
openaire   +2 more sources