most citedWeakly-supervised localization of diabetic retinopathy lesions in retinal fundus images

9 citations · 9 across the 1 of their papers we have counts for

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cs.CV2018

The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution

Muhammad Waleed Gondal, Bernhard Schölkopf, Michael Hirsch

While implicit generative models such as GANs have shown impressive results in high quality image reconstruction and manipulation using a combination of various losses, we consider…

cs.CV2018

Perceptual Video Super Resolution with Enhanced Temporal Consistency

Eduardo Pérez-Pellitero, Mehdi S. M. Sajjadi, Michael Hirsch +1

With the advent of perceptual loss functions, new possibilities in super-resolution have emerged, and we currently have models that successfully generate near-photorealistic high-r…

cs.CV2018

Automatic Estimation of Modulation Transfer Functions

Matthias Bauer, Valentin Volchkov, Michael Hirsch +1

The modulation transfer function (MTF) is widely used to characterise the performance of optical systems. Measuring it is costly and it is thus rarely available for a given lens sp…

cs.CV2017

Learning Blind Motion Deblurring

Patrick Wieschollek, Michael Hirsch, Bernhard Schölkopf +1

As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime. However, taking a quick shot freque…

cs.CV20179 cited

Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images

Waleed M. Gondal, Jan M. Köhler, René Grzeszick +2

Convolutional neural networks (CNNs) show impressive performance for image classification and detection, extending heavily to the medical image domain. Nevertheless, medical expert…