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Found 4 papers, 3 papers with code
Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration
Our approach combines a pre-trained network to extract deep features from the input image with iterative Richardson-Lucy deconvolution steps.
LUCYD: A Feature-Driven Richardson-Lucy Deconvolution Network
Our results demonstrate that LUCYD outperforms the state-of-the-art methods in both synthetic and real microscopy images, achieving superior performance in terms of image quality and generalisability.
Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network
MetaDL Challenge 2020 focused on image classification tasks in few-shot settings.
Unsupervised Latent Space Translation Network
One task that is often discussed in a computer vision is the mapping of an image from one domain to a corresponding image in another domain known as image-to-image translation.
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