data augmentation in CNN

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lech king
lech king 2021-6-24
评论： lech king 2021-6-24
Hello
I am going to train a squeezenet to detect CT scans in two classes of people with covid19 and healthy people, assuming that each image is 512 x 512.
At least in the training phase, how many images should be present so that there is no need to data augmentation like rotation and addition of gaussian and.....

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Walter Roberson
Walter Roberson 2021-6-24
At least 83886080 images for training under the circumstances you describe.
... This should suggest to you that data augmentation is a very important stage.
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lech king
lech king 2021-6-24
Thank you very much
Because I work on CT scans of covid19, which are lung images
In about 70% of cases, the symptoms of the disease appear in certain places
But the reference article I am working on, because it has 441 images in training phase , has thus strengthened its database and achieved 85% accuracy.
a rotation (with a random angle between 0 and 90 degrees), a scale (with a random
value between 1.1 and 1.3) and addition of gaussian noise
to the original image
lech king
lech king 2021-6-24
I use MATLAB Deep Learning application. In this section, rotation and scale can be easily selected.
Thanks for the tips on how to add noise to the original images MATLAB Deep Learning application

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