Howtosignalprocessing
- What is data augmentation in image classification?
- Why data augmentation is important in image classification?
- What is image augmentation technique?
What is data augmentation in image classification?
Image data augmentation is the process of generating new transformed versions of images from the given image dataset to increase its diversity. To a computer, images are just a 2-dimensional array of numbers. These numbers represent pixel values, which you can tweak in many ways to generate new, augmented images.
Why data augmentation is important in image classification?
For image classification
The data augmentation helps in visual transformations. The transformation that is mainly focused on image classification are flipping, color modifications, cropping, rotation, geometric transformation, padding, re-scaling, zooming, gray scaling, darkening and brightening, random erasing etc.
What is image augmentation technique?
Image augmentation is a technique that is used to artificially expand the data-set. This is helpful when we are given a data-set with very few data samples. In case of Deep Learning, this situation is bad as the model tends to over-fit when we train it on limited number of data samples.
