Image Deblurring using GAN

During the training process, two distinct neural networks, namely the Generator and the Discriminator, undergo training. The Generator functions by creating an image through noise filtration via convolution techniques. Meanwhile, the Discriminator evaluates the generated image against the original image during training, aiming to enhance the model's accuracy. This model was tested with test image by applying gaussian noise to the original image and the deblurring accuracy is approximately 85% close to the actual image