1k citations · 1.1k across the 6 of their papers we have counts for
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On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy
Vignesh Srinivasan, Nils Strodthoff, Jackie Ma +3
There is an increasing number of medical use-cases where classification algorithms based on deep neural networks reach performance levels that are competitive with human medical ex…
SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information
Jing Yu Koh, Duc Thanh Nguyen, Quang-Trung Truong +2
Fully-automatic execution is the ultimate goal for many Computer Vision applications. However, this objective is not always realistic in tasks associated with high failure costs, s…
Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles
Alexander Binder, Michael Bockmayr, Miriam Hägele +15
Recent advances in cancer research largely rely on new developments in microscopic or molecular profiling techniques offering high level of detail with respect to either spatial or…
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers
Alexander Binder, Grégoire Montavon, Sebastian Bach +2
Layer-wise relevance propagation is a framework which allows to decompose the prediction of a deep neural network computed over a sample, e.g. an image, down to relevance scores fo…
Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth
Sebastian Bach, Alexander Binder, Klaus-Robert Müller +1
We present an application of the Layer-wise Relevance Propagation (LRP) algorithm to state of the art deep convolutional neural networks and Fisher Vector classifiers to compare th…