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

Capsule Network implementation in Tensorflow

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

Cifar-10 Image Reconstruction using Auto-encoder Models

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.

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.

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

Shape Analysis for AI-Reconstructed Images

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

Reconstructing images using VAE

Audio encoder for reconstruct, denoise image or audio spectrogram

Implementation of "Understanding Deep Image Representations by Inverting Them"

reconstruct the scan image to modify the slipping to horizontal direction