30 citations · 140 across the 23 of their papers we have counts for
7 papers · 1 filter
Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI
Pablo Laso, Stefano Cerri, Annabel Sorby-Adams +21
Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated se…
What do neural networks learn in image classification? A frequency shortcut perspective
Shunxin Wang, Raymond Veldhuis, Christoph Brune +1
Frequency analysis is useful for understanding the mechanisms of representation learning in neural networks (NNs). Most research in this area focuses on the learning dynamics of NN…
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning
Shunxin Wang, Christoph Brune, Raymond Veldhuis +1
Neural networks are prone to learn easy solutions from superficial statistics in the data, namely shortcut learning, which impairs generalization and robustness of models. We propo…
Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space
Ioana Mazilu, Shunxin Wang, Sven Dummer +3
Though modern microscopes have an autofocusing system to ensure optimal focus, out-of-focus images can still occur when cells within the medium are not all in the same focal plane,…
RDA-INR: Riemannian Diffeomorphic Autoencoding via Implicit Neural Representations
Sven Dummer, Nicola Strisciuglio, Christoph Brune
Diffeomorphic registration frameworks such as Large Deformation Diffeomorphic Metric Mapping (LDDMM) are used in computer graphics and the medical domain for atlas building, statis…
A Survey on the Robustness of Computer Vision Models against Common Corruptions
Shunxin Wang, Raymond Veldhuis, Christoph Brune +1
The performance of computer vision models are susceptible to unexpected changes in input images caused by sensor errors or extreme imaging environments, known as common corruptions…
Data-efficient Large Scale Place Recognition with Graded Similarity Supervision
Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov
Visual place recognition (VPR) is a fundamental task of computer vision for visual localization. Existing methods are trained using image pairs that either depict the same place or…