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Can the New Test Data be looped into the Training Data after being Classified by the CNN model?

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Vinay Chawla
Vinay Chawla on 24 Jul 2020
Commented: Vinay Chawla on 27 Jul 2020
I am working on a CNN model but I have a limited dataset to work with. I was wondering if there is a chance that after training the CNN model on a specific number of images, when I test it against a new set of images, these new classified images can be looped into the training set. So that when the model is run again it trains with these new images as a part of the training data set.
Thanks in advance.


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Answers (1)

Harsha Priya Daggubati
Harsha Priya Daggubati on 27 Jul 2020
It is generally advised to keep training and test sets explicit. I can think of one possible workaround, since your dataset is of images, you can augment your dataset using 'imageDataAugmenter' and create an augmentedImageDatastore using it to train your network.
Take a look at these links for more details:
Hope this helps!


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Vinay Chawla
Vinay Chawla on 27 Jul 2020
There is no issue but my study is to classify pavement distresses and the more and varied images I have, the more features the model will learn, because they occur in distinct patterns on different pavements. So,The idea is to expand the training dataset to increase learning and prediction efficiency. If I use the resulting training dataset then the model learns from the same images, correct?

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