This tutorial is based on the SKA Data Challenge 1. The aim of the tutorial is to learn to identify and classify sources is radio images. The data provided is simulated, to represent what the SKA data will look like once the telescope is in operation.
License: BSD 3-Clause "New" or "Revised" License
Why does the number of sources change from a simulated frame to another?
Further, does that mean the frame that produces more sources is better than the others?
We are doing source finding on the whole, and on a training image (cropped from the whole image). Just want to confirm that the sources for the whole images are not included in the training. This can be a problem for assessing the accuracy of machine learning.
Why do we have to crop the image first and then perform source finding separately on the training and the whole image?
Can't we just perform source finding on the whole image and then split the data into training and testing??
Can we add a threshold parameter to the primary beam correction method, so that learners can do further experiments?
we need to add the explanation of What is source finding
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