A high-resolution groundwater map shows how underground water varies across the U.S., with new insights for agriculture and ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

Books with maps are like Captain Flint's buried loot in Robert Louis Stevenson's "Treasure Island"—a rare find, according to ...

Spatial Snippets is our weekly round-up of all the bits and pieces of geospatial news that didn’t make it into our normal ...

Abstract: Quantum computing has reintroduced itself as a breakthrough technology for machine learning, especially in the analysis of massive datasets, especially the genomic ones. The present research ...

R has become a popular and powerful platform for working with geospatial data due to its well-developed ecosystem of packages to import, process, analyze and visualize spatial data, strong integration ...

Floods represent the most frequent natural hazard, generating significant impacts on people as well as considerable economic and environmental losses worldwide. These events are particularly ...

An expert, Yetunde Adesiyan, has called for the development of skills in Geographic Information Science (GIS) and machine learning to tackle real-world challenges. She said in a statement that ...

ABSTRACT: Waste generation in Kenya has been increasing with the rapid urbanization (Haregu et al., 2017; Okot-Okumu, 2012). Almost 50% of the waste is generated in urban centers, and 0.5 kg per ...

In today’s world dominated by artificial intelligence, terms like transformers, LLMs (large language models), and embeddings are everywhere. While many are familiar with models like ChatGPT, few truly ...

Abstract: The purpose of this review is to provide an in-depth bibliometric analysis of Support Vector Machine (SVM) research literature in the field of Artificial Intelligence and Machine Learning in ...