Hyperspectral image compression techniques have become increasingly critical in modern remote sensing, where sensors collect vast spectral cubes composed of hundreds of contiguous bands. These ...

Deep Render, a London startup and spin-out of Imperial College that is applying machine learning to image compression, has raised £1.6 million in seed funding. Leading the round is Pentech, with ...

The CCSDS 122.0-B-1 specification is part of a standards suite developed by the Consultative Committee for Space Data Systems. The CCSDS is formed by the major space agencies of the world for the ...

Deep learning (DL), a class of approaches involving self-learned discriminative features, is increasingly being applied to digital pathology (DP) images for tasks such as disease identification and ...

Large Language Models (LLMs), often recognized as AI systems trained on vast amounts of data to efficiently predict the next part of a word, are now being viewed from a different perspective. A recent ...

Given the image on the left, two study participants made the reconstruction on the right. People preferred their reconstruction to the image at the center, a highly compressed version of the original ...

Optimizing data compression methods has become more critical than ever for cloud storage, data management, and streaming applications. Working with compressed data reduces network bandwidth, data ...

Efficient data compression and transmission are crucial in space missions due to restricted resources, such as bandwidth and storage capacity. This requires efficient data-compression methods that ...

In image compression, a large file that could be cumbersome to store or share loses a small amount of visual information. This "lossiness" largely preserves the image while vastly reducing its file ...

Finding efficient ways to compress and decompress data is more important than ever. Compressed data takes up less space and requires less time and network bandwidth to transfer. In cloud service code, ...