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ENTITY Stacked autoencoders for unsupervised feature learning and multiple organ detection in a pilot study using 4D patient data

Stacked autoencoders for unsupervised feature learning and multiple organ detection in a pilot study using 4D patient data

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    Unsupervised LSTM Autoencoder Enhances IMU Activity Recognition

    Researchers have developed a novel unsupervised framework for human activity recognition using IMU sensors, addressing challenges like reliance on labeled data and complex multi-sensor fusion. The proposed method employ…