Nov 20, 2019 · This paper proposes to use the hidden Markov model for the detection of the transitional instances. It shows experimentally on 35 sleep EEG recordings that ...

Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous Instances · List of references · Publications that cite this publication.

Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous Instances. Proceedings 2019, 31, 46. https://doi.org/10.3390 ...

Macas et al. (2018) demonstrated that for semiautomatic annotation of sleep EEG signals, an AL strategy leads to statistically significantly smaller mean class ...

The main contribution of this paper is to present the design and development of an automated sleep staging system based on the ensemble techniques using single- ...

Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous Instances. Proceedings. 2019-11 | Journal article | Author. DOI ...

Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous Instances ... A complete methodology for semi-automatic sleep scoring ...

Oct 7, 2024 · Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous Instances. UCAmI 2019: 46; 2018. [c12]. view.

Jun 10, 2020 · Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous Instances. Proceedings. 2019;31:46. doi: 10.3390 ...

Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous InstancesActive Learning Approach for EEG Classification using ...