Copertina

Anomaly Detection using Ensemble Classification and Evidence Theory

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Arévalo, Fernando, Ibrahim, Tahasanul, Piolo, Christian Alison M., Schwung, Andreas
Natura:	Preprint
Pubblicazione:	2022
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Information Fusion for Assistance Systems in Production Assessment
di: Arévalo, Fernando, et al.
Pubblicazione: (2023)

Production Assessment using a Knowledge Transfer Framework and Evidence Theory
di: N., Fernando Arevalo, et al.
Pubblicazione: (2022)

Impact of Evidence Theory Uncertainty on Training Object Detection Models
di: Ibrahim, M. Tahasanul, et al.
Pubblicazione: (2024)

Time Series Compression using Quaternion Valued Neural Networks and Quaternion Backpropagation
di: Pöppelbaum, Johannes, et al.
Pubblicazione: (2024)

Transfer learning of state-based potential games for process optimization in decentralized manufacturing systems
di: Yuwono, Steve, et al.
Pubblicazione: (2024)

Self-optimization in distributed manufacturing systems using Modular State-based Stackelberg Games
di: Yuwono, Steve, et al.
Pubblicazione: (2024)

Distributed Stackelberg Strategies in State-based Potential Games for Autonomous Decentralized Learning Manufacturing Systems
di: Yuwono, Steve, et al.
Pubblicazione: (2024)

Stabilizing Multimodal Autoencoders: A Theoretical and Empirical Analysis of Fusion Strategies
di: Altinses, Diyar, et al.
Pubblicazione: (2025)

Layer-Specific Lipschitz Modulation for Fault-Tolerant Multimodal Representation Learning
di: Altinses, Diyar, et al.
Pubblicazione: (2026)

Introducing PetriRL: An Innovative Framework for JSSP Resolution Integrating Petri nets and Event-based Reinforcement Learning
di: Lassoued, Sofiene, et al.
Pubblicazione: (2024)

Gradient-based Learning in State-based Potential Games for Self-Learning Production Systems
di: Yuwono, Steve, et al.
Pubblicazione: (2024)

Data driven feedback linearization of nonlinear control systems via Lie derivatives and stacked regression approach
di: K., Lakshmi Priya P., et al.
Pubblicazione: (2025)

Improving Quaternion Neural Networks with Quaternionic Activation Functions
di: Pöppelbaum, Johannes, et al.
Pubblicazione: (2024)

Stochastic Voronoi Ensembles for Anomaly Detection
di: Cao, Yang, et al.
Pubblicazione: (2026)

Enhancing ECG Classification Robustness with Lightweight Unsupervised Anomaly Detection Filters
di: Ibrahim, Mustafa Fuad Rifet, et al.
Pubblicazione: (2025)

Prior-Informed Neural Network Initialization: A Spectral Approach for Function Parameterizing Architectures
di: Torres, David Orlando Salazar, et al.
Pubblicazione: (2026)

Isolation-based Spherical Ensemble Representations for Anomaly Detection
di: Cao, Yang, et al.
Pubblicazione: (2025)

Anomaly Detection and Classification in Knowledge Graphs
di: Senaratne, Asara, et al.
Pubblicazione: (2024)

Optimal Classification-based Anomaly Detection with Neural Networks: Theory and Practice
di: Zhou, Tian-Yi, et al.
Pubblicazione: (2024)

Improving Anomaly Detection in Industrial Time Series: The Role of Segmentation and Heterogeneous Ensemble
di: Mastriani, Emilio, et al.
Pubblicazione: (2025)

Drift-Aware Variational Autoencoder-based Anomaly Detection with Two-level Ensembling
di: Li, Jin, et al.
Pubblicazione: (2026)

Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly Detection
di: Marimont, Sergio Naval, et al.
Pubblicazione: (2024)

Multivariate Time-series Anomaly Detection via Dynamic Model Pool & Ensembling
di: Hu, Wei, et al.
Pubblicazione: (2026)

Open Challenges in Time Series Anomaly Detection: An Industry Perspective
di: Mueller, Andreas
Pubblicazione: (2025)

A Robust Autoencoder Ensemble-Based Approach for Anomaly Detection in Text
di: Pantin, Jeremie, et al.
Pubblicazione: (2024)

Predicting Wall Thickness Changes in Cold Forging Processes: An Integrated FEM and Neural Network approach
di: Ilic, Sasa, et al.
Pubblicazione: (2024)

Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset
di: Chandekar, Prathamesh, et al.
Pubblicazione: (2025)

Privacy-Preserving Hybrid Ensemble Model for Network Anomaly Detection: Balancing Security and Data Protection
di: Liu, Shaobo, et al.
Pubblicazione: (2025)

SCoNE: Spherical Consistent Neighborhoods Ensemble for Effective and Efficient Multi-View Anomaly Detection
di: Xu, Yang, et al.
Pubblicazione: (2025)

(Implicit) Ensembles of Ensembles: Epistemic Uncertainty Collapse in Large Models
di: Kirsch, Andreas
Pubblicazione: (2024)

Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection
di: Behrendt, Finn, et al.
Pubblicazione: (2024)

Kinematic Detection of Anomalies in Human Trajectory Data
di: Kennedy, Lance, et al.
Pubblicazione: (2024)

Understanding Time Series Anomaly State Detection through One-Class Classification
di: Zhou, Hanxu, et al.
Pubblicazione: (2024)

Quantum Ensemble for Classification
di: Macaluso, Antonio, et al.
Pubblicazione: (2020)

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection
di: Tang, Qideng, et al.
Pubblicazione: (2026)

Statistical Learning Theory for Distributional Classification
di: Fiedler, Christian
Pubblicazione: (2026)

Hierarchical Persistence Velocity for Network Anomaly Detection: Theory and Applications to Cryptocurrency Markets
di: Khormali, Omid
Pubblicazione: (2025)

Improved Anomaly Detection through Conditional Latent Space VAE Ensembles
di: Åström, Oskar, et al.
Pubblicazione: (2024)

Segmentation over Complexity: Evaluating Ensemble and Hybrid Approaches for Anomaly Detection in Industrial Time Series
di: Mastriani, Emilio, et al.
Pubblicazione: (2025)

A Graph-based Framework for Online Time Series Anomaly Detection Using Model Ensemble
di: Yu, Zewei, et al.
Pubblicazione: (2026)