Abstract: Energy-efficiency (EE) is a critical metric within wireless optimization. Power control over fading channels is considered as a promising EE-improving technique, but requires optimization of ...

Abstract: Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning. Traditional manifold learning, as a typical ...

When and where the next large earthquake will strike remains one of the most difficult questions in geoscience. Researchers ...

In this work, we propose an unsupervised deep learning model to address multi-focus image fusion problem. First, we train an encoder-decoder architecture in unsupervised manner to acquire deep feature ...

Designing an unsupervised image denoising approach in practical applications is a challenging task due to the complicated data acquisition process. In the realworld case, the noise distribution is so ...

As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability ...

Everyone knows that water has unusual behavior: it becomes less dense when freezing, allowing ice to float. But this ...

Howdy, pards, here's a quick roundup of the week's science news: Moose, previously thought to be a transplanted species, are ...

A steer-by-wire bicycle reliably distinguishes between cornering and unstable riding conditions, enhancing riding safety.

The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...

Explore how AI phenotypic screening transforms image-based drug discovery through advanced phenotypic data analysis and ML-driven cell-based assays.

Overview AI and big data posted the sharpest jump on WEF's 2025 skills ranking, up 17 percentage points in two years, while ...