Convolutional neural networks (CNNs) have recently achieved remarkable performance in positron emission tomography (PET) image reconstruction. In particular, CNN-based PET image reconstruction, which ...

This study introduces the hierarchical pixel-wavelength fusion network (HPWF-Net), a novel hyperspectral reconstruction framework designed to address the challenges of tree species classification and ...

A novel neural network for preserving cultural heritage via 3D image reconstruction Date: October 31, 2024 Source: Ritsumeikan University Summary: Relief-type cultural heritage objects are ...

By utilizing 'super-resolved' latent information during training, NeuPh achieves scalable and generalizable high-resolution image reconstruction from low-resolution intensity images, applicable to a ...

This repository provides the source code for the paper "Exact reconstruction and reconstruction from noisy data with anisotropic total variation" as cited below.

How can high-quality 3D reconstructions be achieved from a limited number of images? A team of researchers from Columbia University and Google introduced ‘ReconFusion,’ An artificial intelligence ...

Description Image Processing in Python for 3D image stacks, or IMPPY3D, is a software repository comprising mostly Python scripts that simplify post-processing and 3D shape characterization of ...

The most recent notable video reconstruction study by Han et al. (2019) made use of a variational auto-encoder and was able to reconstruct low-level properties of the images, where the reconstructions ...