Reconstructing images using VAE
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Updated
Dec 22, 2018 - Jupyter Notebook
Reconstructing images using VAE
Using optimizations algorithms to reconstruct images from a set of basic shapes
Audio encoder for reconstruct, denoise image or audio spectrogram
Implementation of "Understanding Deep Image Representations by Inverting Them"
Cifar-10 Image Reconstruction using Auto-encoder Models
reconstruct the scan image to modify the slipping to horizontal direction
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.
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.
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.
Shape Analysis for AI-Reconstructed Images
Capsule Network implementation in Tensorflow
A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.
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