Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to
alleviate the burden on radiologists and MR technologists, and improve throughput. The …

Above-ground biomass (AGB) serves as an indicator of crop growth status, and acquiring
timely AGB information is crucial for estimating crop yield and determining appropriate water …

The fruit quality and yield of sweet peppers can be effectively improved by accurately and
efficiently controlling the growth conditions and taking timely corresponding measures to …

Crop yield prediction is critical for investigating the yield gap and potential adaptations to
environmental and management factors in arid regions. Crop models (CMs) are powerful …

The growing global requirement for food and the need for sustainable farming in an era of a
changing climate and scarce resources have inspired substantial crop yield prediction …

Wheat's nutritional value is critical for human nutrition and food security. However, more
attention is needed, particularly regarding the content and concentration of iron (Fe) and …

Evapotranspiration (ETo) is one of the most important processes in the hydrologic cycle, with
specific application to sustainable water resource management. As such, this study aims to …

Traditional simulation models are often point based; thus, more research is needed to
emphasize spatial simulation, providing decision‐makers with fast recommendations …

This study focuses on an ad hoc machine-learning method for locating archaeological sites
in arid environments. Pleiades (P1B) were uploaded to the cloud asset of the Google Earth …

A methodology is presented for the quantitative assessment of soil biomass productivity at
100 m spatial resolution on a national scale. The traditional land evaluation approach …