In this paper, we show the strength of the transformer architecture with regard to generalization capability over the conventional CNN architecture in sleep ...
Sep 25, 2024 · This study proposes an innovative deep learning framework that enhances sleep stage classification by integrating self-attention mechanisms and Conditional ...
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In this paper, we show the strength of the transformer architecture with regard to generalization capability over the conventional. CNN architecture in sleep ...
Sep 7, 2024 · However, in this paper, we find that the transformer architecture has better generalization capability to capture the features from data samples ...
Sep 10, 2024 · ... Limiting It to Improve Performance ... Improved Generalization from Limiting Attention in a Transformer for Sleep Stage Classification.
Dongyoung Kim's 14 research works with 46 citations, including: Improved Generalization from Limiting Attention in a Transformer for Sleep Stage Classification.
Sep 23, 2024 · In this paper, we will systematically review SSC research based on DL methods (DL-SSC). We explores DL-SSC from several important perspectives.
This study aimed to develop a deep learning model that addresses generalization problems by integrating enzyme-inspired specificity and employing separating ...
Oct 11, 2024 · The enhanced features are classified via two fully connected layers, yielding substantial improvements in sleep stage classification accuracy ...
Jun 10, 2020 · We propose a neural network based on a convolutional network (CNN) and attention mechanism to perform automatic sleep staging.