SoFFT uses spatial Fourier transform on Cosserat rod backbones to compactly model soft robot deformations, unifying heuristics and enabling experimental data-driven methods with fewer parameters.
Atomic decomposition by basis pursuit,
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CSEN is a compact convolutional neural network trained to estimate sparse support sets directly from measurements, claiming state-of-the-art accuracy at lower computational cost than iterative methods.
Introduces CSEN, a non-iterative network bridging sparse representation and deep learning, for Covid-19 detection from X-ray images with limited training data.
Hard-thresholding AMP for indoor THz channel estimation outperforms prior methods and approaches oracle performance.
citing papers explorer
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SoFFT: Spatial Fourier Transform for Modeling Continuum Soft Robots
SoFFT uses spatial Fourier transform on Cosserat rod backbones to compactly model soft robot deformations, unifying heuristics and enabling experimental data-driven methods with fewer parameters.
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Convolutional Sparse Support Estimator Network (CSEN) From energy efficient support estimation to learning-aided Compressive Sensing
CSEN is a compact convolutional neural network trained to estimate sparse support sets directly from measurements, claiming state-of-the-art accuracy at lower computational cost than iterative methods.
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Convolutional Sparse Support Estimator Based Covid-19 Recognition from X-ray Images
Introduces CSEN, a non-iterative network bridging sparse representation and deep learning, for Covid-19 detection from X-ray images with limited training data.
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Approximate Message Passing for Indoor THz Channel Estimation
Hard-thresholding AMP for indoor THz channel estimation outperforms prior methods and approaches oracle performance.