Plant phenotyping has been recognized as a bottleneck for improving the efficiency of
breeding programs, understanding plant-environment interactions, and managing …

The number of objects is considered an important factor in a variety of tasks in the
agricultural domain. Automated counting can improve farmers' decisions regarding yield …

Neural networks have become increasingly prevalent within the geosciences, although a
common limitation of their usage has been a lack of methods to interpret what the networks …

The intensification of extreme precipitation under anthropogenic forcing is robustly projected
by global climate models, but highly challenging to detect in the observational record. Large …

Artificial intelligence (AI) has emerged as a fundamental component of global agricultural
research that is poised to impact on many aspects of plant science. In digital phenomics, AI …

Among the maintenance policies adopted to guarantee the safety of structures throughout
their service life, condition-based maintenance policies driven by structural health …

Flower and fruit count is a critical metric in developing crop-load management and
harvesting strategies during flower/fruit development and harvest seasons. Growers …

In this paper, we propose a novel approach to model spatial heterogeneity for epidemic
spreading, which combines the relevance of transport proximity in human movement and the …

The deep learning (DL) model has performed successfully in various fields, including
manufacturing. DL models for defect image data analysis in the manufacturing field have …

Artificial Intelligence (AI) is increasingly used within plant science, yet it is far from being
routinely and effectively implemented in this domain. Particularly relevant to the …