Image Augmentation

Image Augmentation is the technique of artificially creating more data by altering the existing ones. This manipulation involves operations like shifts, flips, zooms etc.

Advantages:

• It expands the training dataset.

• It can prevent overfitting

• It can add to the generalisation of the model

• The model becomes spatially invariant.

Limitations:

• Requires evaluation of the created data.

• The biases in real data are also reflected in augmented data.