Image Augmentation

Image augmentation is a technique used to increase the variety of images in a dataset by making small modifications, such as rotating, flipping, cropping, or adjusting brightness. This helps machine learning models learn better by exposing them to different versions of the same image, improving their ability to recognize patterns regardless of changes in appearance. It's like practicing with different angles and lighting conditions to become better at identifying objects, which makes the model more robust and accurate in real-world scenarios.