Paper Title: Interactive Reconstruction of Monte Carlo Image Sequences using a Recurrent Denoising Autoencoder Authors: Chakravarty R. Alla Chaitanya, Anton S. Kaplanyan, Christoph Schied, Marco Salvi ...

Um denoising autoencoder é uma variação onde o modelo é treinado para reconstruir uma entrada limpa a partir de uma versão corrompida dessa mesma entrada. Isso os torna eficazes para tarefas de ...

Ideally, any suitable denoising autoencoder can be used, but we adopt the U-Net architecture (Ronneberger et al., 2015) originally developed for medical imaging applications and is robust for various ...

We demonstrate the use of a Convolutional Denoising Autoencoder Neural Network to denoise Hyperspectral Stimulated Raman Scattering microscopy images.

SeBiReNet (Nie et al., 2020) is a Siamese denoising autoencoder tested on feature disentanglement, pose denoising, and unsupervised cross-view HAR. According to Paoletti et al. (2021b), unsupervised ...

We investigate the impact of noise on time-reversal imaging and propose an approach that significantly enhances the detection of objects in noisy environments. Our method involves the decomposition of ...