A team of researchers at ETH Zurich are working on a novel approach to solving increasingly large graph problems. Large graphs are a basis of many problems in social sciences (e.g., studying human ...

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 ...

Compression is the science of making data representations smaller, in order to decrease the data's bandwidth and storage requirements. Compression applications are everywhere: in computers (WinZip and ...

ADCs and DACs are generating a flood of sampled data that are creating high-speed bottlenecks on busses and in networks. Part 1 of this article described the use of compression algorithms that take ...

Compression algorithms for speech, audio, still images, and video are quite complicated and, more importantly, nearly always lossy. Thus, samples often change dramatically once they’re decompressed.

Innovative compression algorithms can improve today�s high-speed data sampling. Compression algorithms have enabled many popular applications over the years. We cannot imagine sending e-mail ...

It used to be that memory and storage space were so precious and so limited of a resource that handling nontrivial amounts of text was a serious problem. Text compression was a highly practical ...

Lossless or lossy: If you have big data, know what type of compression to use Your email has been sent Illustration: Lisa Hornung/iStockPhoto Must-read big data coverage What Powers Your Databases?