3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in sleep-spindles-detection-4
Use these libraries to find sleep-spindles-detection-4 models and implementations
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A generative model for single-channel EEG that incorporates the constraints experts actively enforce during visual scoring and derives algorithms for exact, tractable inference as a special case of Generalized Expectation Maximization via dynamic programming and backpropagation.
A U-Net-type deep neural network model is presented that exceeds that of the state-of-the-art detector and of most experts in the MODA dataset and shows improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably.
Adding a benchmark result helps the community track progress.