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Found 7 papers, 2 papers with code
Learned, Uncertainty-driven Adaptive Acquisition for Photon-Efficient Multiphoton Microscopy
Finally, with our adaptive acquisition technique, we demonstrate a 120X reduction in acquisition time and total light dose while successfully recovering fine features in the sample.
Dancing under the stars: video denoising in starlight
To enable this, we develop a GAN-tuned physics-based noise model to more accurately represent camera noise at the lowest light levels.
Ranked #7 on
Image Denoising
on SID x300
Untrained networks for compressive lensless photography
We demonstrate our untrained approach on lensless compressive 2D imaging as well as single-shot high-speed video recovery using the camera's rolling shutter, and single-shot hyperspectral imaging.
Miniscope3D: optimized single-shot miniature 3D fluorescence microscopy
Miniature fluorescence microscopes are a standard tool in systems biology.
Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array
Hyperspectral imaging is useful for applications ranging from medical diagnostics to agricultural crop monitoring; however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption.
Unrolled, model-based networks for lensless imaging
Various reconstruction methods are explored, on a scale from classic iterative approaches (based on the physical imaging model) to deep learned methods with many learned parameters.
Learned reconstructions for practical mask-based lensless imaging
In this work, we address these limitations using a bounded-compute, trainable neural network to reconstruct the image.
