Why Is Data Augmentation Important?
Understand the role of data augmentation in enhancing object detection models by increasing training data diversity. Explore techniques like rotation, flipping, cropping, and noise addition that help models generalize better to unseen data while reducing overfitting and improving robustness to environmental variations.
Let’s imagine going into a secluded, unexplored forest with various species of plants and trees that we’ve never seen before. But still, just by looking at them, we can identify them as trees. Wouldn’t it be great to train our model to recognize objects in a way that it performs brilliantly on unseen data, just like a human does?
We know that it is impossible to include all the variations of real-world data in our training set. This is where data augmentation comes into play, which is a technique that adds creative variations to our training data, making our model more versatile and powerful.
There are many different ways to ...