The article introduces a new way to add padding to images in neural networks, called learning-based padding. Instead of using simple padding methods like adding zeros, this approach calculates padding based on the image's borders. By using two different modules, LPC and LPA, the researchers found that this new padding technique consistently improves accuracy in tasks like image classification and segmentation compared to traditional padding methods. The codes and trained modules are available for use.