Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We
have created various computer-mediated virtual environments, including social networks …

Spatial transcriptomics (ST) has demonstrated enormous potential for generating intricate
molecular maps of cells within tissues. Here we present iStar, a method based on …

Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …

A major challenge when using k-means clustering often is how to choose the parameter k,
the number of clusters. In this letter, we want to point out that it is very easy to draw poor …

Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …

Despite its technological benefits, the Internet of Things (IoT) has cyber weaknesses due to
vulnerabilities in the wireless medium. Machine Larning (ML)-based methods are widely …

This paper investigates the effective utilization of unlabeled data for large-area cross-view
geo-localization (CVGL) encompassing both unsupervised and semi-supervised settings …

Machine learning techniques have deeply rooted in our everyday life. However, since it is
knowledge-and labor-intensive to pursue good learning performance, humans are heavily …

It has long been observed that for practically any computational problem that has been
intensely studied, different instances are best solved using different algorithms. This is …