Random Cropping

Random cropping is a technique often used in image processing and machine learning. It involves selecting a random portion of an image to keep while discarding the rest. This is done to create variations of the image, helping a model learn from different perspectives and details. By exposing the model to these different sections, it becomes better at recognizing patterns, objects, or features in images despite variations in appearance. Essentially, random cropping helps improve the robustness and accuracy of image recognition systems by enriching the training data with diverse views of the same content.