Robust R2D2 DNN series for monochromatic intensity imaging with VLA
收藏DataCite Commons2025-02-27 更新2025-04-16 收录
下载链接：
https://researchportal.hw.ac.uk/en/datasets/e3060b95-4fe6-4b61-9f72-d77653c305bb
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资源简介：
The dataset consists of R2D2 DNN series underpinned by two core architectures: U-Net and the U-WDSR. The proposed novel U-WDSR architecture integrates the WDSR residual body with the U-Net framework. These models are specifically trained to reconstruct monochromatic intensity radio images of size up to 512x512 from radio-interferometric data acquired by the Very Large Array (VLA), accommodating various data-weighting schemes and angular resolutions (i.e., pixel sizes). Five realisations of each DNN series are provided, described as follows:
1. R2D2_{A1, T2}: A series of 25 DNNs using U-Net as the core architecture.
2. R2D2_{A1, T2}: A series of 25 DNNs using U-WDSR as the core architecture.
All DNN models are provided as PyTorch models for use in Python environments.
提供机构：
Heriot-Watt University
创建时间：
2025-02-27
