Conservation of biodiversity is critical for the coexistence of humans and the sustenance of
other living organisms within the ecosystem. Identification and prioritization of specific …

Progress in deep learning, more specifically in using convolutional neural networks (CNNs)
for the creation of classification models, has been tremendous in recent years. Within …

Biodiversity is in crisis globally, and we consistently fail to hit global targets to stem its loss.
Inspired by the Kunming‐Montreal Global Biodiversity Framework, the biodiversity credit …

The conventional process of building Ontologies and Knowledge Graphs (KGs) heavily
relies on human domain experts to define entities and relationship types, establish …

Mosquito-borne diseases account for human morbidity and mortality worldwide, caused by
the parasites (eg, malaria) or viruses (eg, dengue, Zika) transmitted through bites of infected …

Artificial intelligence (AI) is revolutionizing biodiversity research by enabling advanced data
analysis, species identification, and habitats monitoring, thereby enhancing conservation …

BACKGROUND The yellow‐legged hornet (Vespa velutina) is native to Southeast Asia and
is an invasive alien species of concern in many countries. More effective management of …

Mountain meadows are an essential part of the alpine–subalpine ecosystem; they provide
ecosystem services like pollination and are home to diverse plant communities. Changes in …

Artificial Intelligence (AI) is revolutionizing biodiversity research by enabling advanced data
analysis, species identification, and habitats monitoring, thereby enhancing conservation …

Background Recently, machine learning (ML) has been widely used in species auto-
identification systems for multi-scene applications in biodiversity, while most of the existing …