Machine Learning and Deep Learning models make life easier when it comes to data processing and extracting relevant information out of it. However, a very prominent limitation of utilizing deep learning models for processing is that unless you have a huge data set, the creation of a learning model becomes extremely difficult. Having said that, manually processing even seemingly small documents is easier said than done. Thus, one thing is clear that we would require a learning model to get the job done, but the question is how.
To resolve this issue, a concept was developed where additional data is created from the existing sets, thereby creating more information to feed the deep learning model such that it can be implemented to process our data. This technique is called Image Augmentation. To know how this methodology works and why it is becoming increasingly popular, keep reading till the end and learn everything you need to know about image/data augmentation.