7 citations · 20 across the 15 of their papers we have counts for
44 papers
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization
Christina Runkel, Christian Etmann, Michael Möller +1
An increasing number of models require the control of the spectral norm of convolutional layers of a neural network. While there is an abundance of methods for estimating and enfor…
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
Tao Wei, Angelica I Aviles-Rivero, Shuo Wang +4
The task of classifying mammograms is very challenging because the lesion is usually small in the high resolution image. The current state-of-the-art approaches for medical image c…
Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding
Veronica Corona, Yehuda Dar, Guy Williams +1
The Magnetic Resonance Imaging (MRI) processing chain starts with a critical acquisition stage that provides raw data for reconstruction of images for medical diagnosis. This flow…
A Linear Transportation Distance for Pattern Recognition
Oliver M. Crook, Mihai Cucuringu, Tim Hurst +3
The transportation distance, denoted , has been proposed as a generalisation of Wasserstein distances motivated by the property that it…
Unsupervised Image Restoration Using Partially Linear Denoisers
Rihuan Ke, Carola-Bibiane Schönlieb
Deep neural network based methods are the state of the art in various image restoration problems. Standard supervised learning frameworks require a set of noisy measurement and cle…
Scanning electron diffraction tomography of strain
Robert Tovey, Duncan N. Johnstone, Sean M. Collins +4
Strain engineering is used to obtain desirable materials properties in a range of modern technologies. Direct nanoscale measurement of the three-dimensional strain tensor field wit…