The autoencoder structure is simple, consisting of: Encoder : A single linear layer that compresses the 784-dimensional input down to a latent space. Decoder : A single linear layer that reconstructs ...

At 1 sample per pixel (spp), the Monte Carlo integration of indirect illumination results in very noisy images, and the problem can therefore be framed as reconstruction instead of denoising. Previous ...

Traditional DL-based denoising requires pairs of noisy input and corresponding clean targets, which are impractical to obtain in real-world wireless networks. To address this challenge, we propose a ...

Abstract: We propose Denoising Masked Autoencoder (Deno-MAE), a novel multimodal autoencoder framework for denoising modulation signals during pretraining. DenoMAE extends the concept of masked ...

Este projeto implementa um Autoencoder Denoising utilizando a biblioteca Keras para remover ruído de imagens de dígitos manuscritos. O modelo é treinado no dataset MNIST, onde imagens originais são ...