Wavelet-CNN

This project is an implementation of the paper Wavelet Integrated CNNs for Noise Robust Image Classification which aims to improve the robustness of convolutional neural networks (CNNs) for image classification tasks, particularly for noisy images. By integrating discrete wavelet transform (DWT) layers into popular CNN architectures, such as AlexNet and VGG, they aim to improve model performance on noisy images.