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Novelty Detection Using Level Set Methods

  • Published:2015-03 Issue:3 Volume:26 Page:576-588
  • ISSN:2162-237X
  • Container-title:IEEE Transactions on Neural Networks and Learning Systems
  • language:
  • Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Xuemei Ding ,Yuhua Li ,Belatreche Ammar,Maguire Liam P.

Funder

University of Ulster Vice Chancellors Research Scholarship Scheme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Distance-based novelty detection model for identifying individuals at risk of developing Alzheimer's disease;Frontiers in Aging Neuroscience;2024-04-15

2. A Deep Learning-Based Hybrid Model for Optimal Anomaly Detection;2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE);2023-07-24

3. Learning Spatial Graph Structure for Multivariate KPI Anomaly Detection in Large-Scale Cyber-Physical Systems;IEEE Transactions on Instrumentation and Measurement;2023

4. Integrated Autoencoder-Level Set Method Outperforms Autoencoder for Novelty Detection;2022 International Joint Conference on Neural Networks (IJCNN);2022-07-18

5. SPiForest: An Anomaly Detecting Algorithm Using Space Partition Constructed by Probability Density-Based Inverse Sampling;IEEE Transactions on Neural Networks and Learning Systems;2022
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