Coordinate Independent Convolutional Networks--Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

M Weiler, P Forré, E Verlinde, M Welling - arxiv preprint arxiv:2106.06020, 2021 - arxiv.org
Motivated by the vast success of deep convolutional networks, there is a great interest in
generalizing convolutions to non-Euclidean manifolds. A major complication in comparison …

Effective rotation-invariant point cnn with spherical harmonics kernels

A Poulenard, MJ Rakotosaona, Y Ponty… - … Conference on 3D …, 2019 - ieeexplore.ieee.org
We present a novel rotation invariant architecture operating directly on point cloud data. We
demonstrate how rotation invariance can be injected into a recently proposed point-based …

[HTML][HTML] Roto-translation equivariant convolutional networks: Application to histopathology image analysis

MW Lafarge, EJ Bekkers, JPW Pluim, R Duits… - Medical Image …, 2021 - Elsevier
Rotation-invariance is a desired property of machine-learning models for medical image
analysis and in particular for computational pathology applications. We propose a …

Rotation invariance and equivariance in 3D deep learning: a survey

J Fei, Z Deng - Artificial Intelligence Review, 2024 - Springer
Deep neural networks (DNNs) in 3D scenes show a strong capability of extracting high-level
semantic features and significantly promote research in the 3D field. 3D shapes and scenes …

Standardised convolutional filtering for radiomics

A Depeursinge, V Andrearczyk, P Whybra… - arxiv preprint arxiv …, 2020 - arxiv.org
The Image Biomarker Standardisation Initiative (IBSI) aims to improve reproducibility of
radiomics studies by standardising the computational process of extracting image …

Neural networks enforcing physical symmetries in nonlinear dynamical lattices: The case example of the Ablowitz–Ladik model

W Zhu, W Khademi, EG Charalampidis… - Physica D: Nonlinear …, 2022 - Elsevier
In this work we introduce symmetry-preserving, physics-informed neural networks (S-PINNs)
motivated by symmetries that are ubiquitous to solutions of nonlinear dynamical lattices …

Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI

C Russo, S Liu, A Di Ieva - Medical & Biological Engineering & Computing, 2022 - Springer
Abstract Magnetic Resonance Imaging (MRI) is used in everyday clinical practice to assess
brain tumors. Deep Convolutional Neural Networks (DCNN) have recently shown very …