A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.

Reconstruction d'une image médicale par l'usage de la transformée inverse de Radon sur les données d'atténuation des radiations traversant le tissu biologique.

Reconstructing images using VAE

Capsule Network implementation in Tensorflow

Audio encoder for reconstruct, denoise image or audio spectrogram

reconstruct the scan image to modify the slipping to horizontal direction

This project was completed in 2018 as a part of my postgraduate studies in Biomedical Engineering

Image Encoding software in MATLAB. Quantize and Dequantize Image and using of Huffman encoding to transform Images to bitstreams according to JPEG universal standard.

Implementation of "Understanding Deep Image Representations by Inverting Them"

Shape Analysis for AI-Reconstructed Images

Using optimizations algorithms to reconstruct images from a set of basic shapes

Cifar-10 Image Reconstruction using Auto-encoder Models

Implementation of the paper LEARN: Learned Experts’ Assessment-based Reconstruction Network for Sparse-data CT Hu Chen, Yi Zhang, Yunjin Chen, et. al

Supplementary material for the paper "Lightweight Multitask Learning for Robust JND Prediction using Latent Space and Reconstructed Frames", IEEE TCSVT, 2024.