Breaking tunnel vision, imaging AI lifts fluorescence image restoration accuracy and speed

Recent years have witnessed great advances in applying deep learning to improve fluorescence microscopy imaging. However, enhancing the fidelity of image restoration networks and improving their ...
GitHub

DAM-VSR: Disentanglement of Appearance and Motion for Video Super-Resolution (ACM SIGGRAPH 2025)

conda create -n dam-vsr python=3.10.14 conda activate dam-vsr pip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org ...
IEEE

Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI

Abstract: Objective: To introduce an MRI in-plane resolution enhancement method that estimates High-Resolution (HR) MRIs from Low-Resolution (LR) MRIs. Method & Materials: Previous CNN-based MRI super ...
IEEE

Model Inspired Autoencoder for Unsupervised Hyperspectral Image Super-Resolution

Abstract: This article focuses on hyperspectral image (HSI) super-resolution that aims to fuse a low-spatial-resolution HSI and a high-spatial-resolution multispectral image to form a ...
Europe PMC

Dilated projection correction network based on autoencoder for hyperspectral image super-resolution.

This paper focuses on improving the spatial resolution of the hyperspectral image (HSI) by taking the prior information into consideration. In recent years, single HSI super-resolution methods based ...