3 papers
cs.CV2026
Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural network
Wenzhao Zhao, Barbara D. Wichtmann, Steffen Albert +3
Group-equivariant convolutional neural networks (G-CNN) heavily rely on parameter sharing to increase CNN's data efficiency and performance. However, the parameter-sharing strategy…
cs.CV2026
Efficient 3D affinely equivariant CNNs with adaptive fusion of augmented spherical Fourier-Bessel bases
Wenzhao Zhao, Steffen Albert, Barbara D. Wichtmann +4
Filter-decomposition-based group equivariant convolutional neural networks (CNNs) have shown promising stability and data efficiency for 3D image feature extraction. However, these…
cs.CV2025
A baseline for machine-learning-based hepatocellular carcinoma diagnosis using multi-modal clinical data
Binwu Wang, Isaac Rodriguez, Leon Breitinger +9
The objective of this paper is to provide a baseline for performing multi-modal data classification on a novel open multimodal dataset of hepatocellular carcinoma (HCC), which incl…