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Found 4 papers, 2 papers with code
Photon-counting CT using a Conditional Diffusion Model for Super-resolution and Texture-preservation
Ultra-high resolution images are desirable in photon counting CT (PCCT), but resolution is physically limited by interactions such as charge sharing.
Decorrelative Network Architecture for Robust Electrocardiogram Classification
We propose a novel ensemble approach based on feature decorrelation and Fourier partitioning for teaching networks diverse complementary features, reducing the chance of perturbation-based fooling.
Disrupting Adversarial Transferability in Deep Neural Networks
Furthermore, we show how applying a feature correlation loss, which decorrelates the extracted features in a latent space, can reduce the transferability of adversarial attacks between models, suggesting that the models complete tasks in semantically different ways.
Simultaneous reconstruction of the initial pressure and sound speed in photoacoustic tomography using a deep-learning approach
Photoacoustic tomography seeks to reconstruct an acoustic initial pressure distribution from the measurement of the ultrasound waveforms.
