The automation of fossil pollen analysis promises many advantages in handling large
numbers of samples with less resource allocation. However, automation is often obstructed …

In the past few decades, numerous electrocatalyst design studies have been reported.
Although machine learning (ML) has recently emerged as a more efficient alternative to …

This review explores the comparative utility of machine learning (ML) and deep learning
(DL) in land system science (LSS) classification tasks. Through a comprehensive …

Most industrial workplaces involving robots and other apparatus operate behind the fences
to remove defects, hazards, or casualties. Recent advancements in machine learning can …

Information on geo-locations of renewable energy installations is very useful to investigate
spatial, social or environmental questions on their impact at local and national level …

In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities
across a wide array of text-centric tasks. However, theirlarge'scale introduces significant …

Inevitably, various errors occur in an actual storage ring, such as magnetic field errors,
magnet misalignments, and ground settlement deformation, which cause closed orbit …

Purpose The main purpose in this study is to propose a transfer learning-based method for
COVID-19 detection from recently collected and challenging database of Computed …

The spiking neural P systems (SNP systems) research area is a typical one for bioinspired
branches of computer science, illustrating many more general features of this scientific …

The application of machine learning and remote sensing techniques to estimate crop yield
has garnered significant attention due to their ability to analyze large volumes of data and …