This work introduces the application of alchemical free energy predictions to estimate PTM impacts on bioactivity and investigates the current errors that limit their practical use in clinical ...

In this paper, we develop a new parallel implementation of the iterative error analysis (IEA) algorithm for lossy hyperspectral image compression on graphics pr ...

This repo is the official implementation of CVPR 2025 paper: MambaIC: State Space Models for High-Performance Learned Image Compression MambaIC: State Space Models for High-Performance Learned Image ...

ROI-Packing is a novel approach to image compression for machine vision. By selecting important regions and packing them together, it eliminates underutilized space to improve compression and ...

They divided the plain image into blocks and compressed and preencrypted it using block compressive sensing. The authors embedded the cipher image onto the carrier image using the singular value ...

The accuracy of computational models of water is key to atomistic simulations of biomolecules. We propose a computationally efficient way to improve the accuracy of the prediction of hydration-free ...

CS theory breaks through Nyquist’s theorem, and it is a pre-processing technique that exploits the signal’s sparsity for sampling the data (Zhang et al., 2022). CS is more hardware-friendly, ...