Patchdrivenet

Patch-Driven-Net is a deep learning-based image processing approach that leverages the power of CNNs to process images in a patch-wise manner. The core idea behind Patch-Driven-Net is to divide an input image into small patches, process each patch independently using a CNN, and then aggregate the results to form the final output. This patch-wise processing approach allows Patch-Driven-Net to effectively capture local patterns and textures in images, leading to improved performance in various image processing tasks.