151 citations · 488 across the 19 of their papers we have counts for
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Fully Unsupervised Probabilistic Noise2Void
Mangal Prakash, Manan Lalit, Pavel Tomancak +2
Image denoising is the first step in many biomedical image analysis pipelines and Deep Learning (DL) based methods are currently best performing. A new category of DL methods such…
Leveraging Self-supervised Denoising for Image Segmentation
Mangal Prakash, Tim-Oliver Buchholz, Manan Lalit +3
Deep learning (DL) has arguably emerged as the method of choice for the detection and segmentation of biological structures in microscopy images. However, DL typically needs copiou…
Probabilistic Noise2Void: Unsupervised Content-Aware Denoising
Alexander Krull, Tomas Vicar, Florian Jug
Today, Convolutional Neural Networks (CNNs) are the leading method for image denoising. They are traditionally trained on pairs of images, which are often hard to obtain for practi…