Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions von Bench, Ciaran, Hauptmann, Andreas, Cox, Ben

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Large-scale electrophysiology and deep learning reveal distorted neural signal dynamics after hearing loss von Sabesan, Shievanie, Fragner, Andreas, Bench, Ciaran, Drakopoulos, Fotios, Lesica, Nicholas A

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Modeling Fibrillogenesis of Collagen-Mimetic Molecules von Hafner, Anne E., Gyori, Noemi G., Bench, Ciaran A., Davis, Luke K., Šarić, Anđela

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Limitations of effective medium models for tissue phantoms in the THz frequency range von Saxena, Sonal, Bench, Ciaran, Garg, Diksha, Boardman, Patric, Mrnka, Michal, Penketh, Harry, Stone, Nicholas, Hendry, Euan

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Data-driven quantitative photoacoustic tomography von Bench, Ciaran

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Unsupervised segmentation of biomedical hyperspectral image data: tackling high dimensionality with convolutional autoencoders von Bench, Ciaran, Nallala, Jayakrupakar, Wang, Chun-Chin, Sheridan, Hannah, Stone, Nicholas

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Enhancing synthetic training data for quantitative photoacoustic tomography with generative deep learning von Bench, Ciaran, Cox, Ben T

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Unsupervised denoising of Raman spectra with cycle-consistent generative adversarial networks von Bench, Ciaran, Bergholt, Mads S, al-Badri, Mohamed Ali

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Enhancing synthetic training data for quantitative photoacoustic tomography with generative deep learning von Bench, Ciaran, Cox, Ben T

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Towards accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in 3D von Bench, Ciaran, Hauptmann, Andreas, Cox, Ben

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Large-scale electrophysiology and deep learning reveal distorted neural signal dynamics after hearing loss von Sabesan, Shievanie, Fragner, Andreas, Bench, Ciaran, Drakopoulos, Fotios, Lesica, Nicholas A

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Unsupervised segmentation of biomedical hyperspectral image data: tackling high dimensionality with convolutional autoencoders von Bench, Ciaran, Nallala, Jayakrupakar, Wang, Chun-Chin, Sheridan, Hannah, Stone, Nicholas

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Unsupervised denoising of Raman spectra with cycle-consistent generative adversarial networks von Bench, Ciaran, Bergholt, Mads S, Mohamed Ali al-Badri

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Towards accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in 3D von Bench, Ciaran, Hauptmann, Andreas, Cox, Ben

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Unsupervised segmentation of biomedical hyperspectral image data: tackling high dimensionality with convolutional autoencoders von Bench, Ciaran, Nallala, Jayakrupakar, Chun-Chin, Wang, Sheridan, Hannah, Stone, Nicholas

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