Group Equivariant Convolutional Neural Networks for Color Fundus Images Super-ResolutionDownload PDF

13 Sept 2022, 16:18 (modified: 03 Mar 2023, 09:16)GeoMedIA (Extended abstracts) PosterReaders: Everyone
Keywords: Fundus images, Super-resolution, Group Equivariant Convolution Neural Networks, MSRResNet
TL;DR: Proposed a MSRResNet with Group Equivariant Convolution Neural Networks for fundus images super-resolution
Abstract: High-resolution (HR) color fundus images can provide finer details and help with a more accurate diagnosis, while deep learning-based super-resolution methods usually require a large amount of data. This paper integrated Group Equivariant Convolution Neural Networks (G-CNNs) in Modified SRResNet (MSRResNet) for fundus images super-resolution. Experiments showed that it leads to some improvement compared with regular CNNs.
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