Premise Quantitative plant traits play a crucial role in biological research. However,
traditional methods for measuring plant morphology are time consuming and have limited …

Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the
study of evolutionary morphology. While classical AI methods such as principal component …

Image‐based machine learning tools are an ascendant 'big data'research avenue. Citizen
science platforms, like iNaturalist, and museum‐led initiatives provide researchers with an …

Artificial intelligence (AI) is poised to transform many aspects of society, and the study of
evolutionary morphology is no exception. Classical AI methods such as Principal …

Metadata management plays a critical role in data governance, resource discovery, and
decision-making in the data-driven era. While traditional metadata approaches have …

Researchers seeking to apply computational methods are increasingly turning to scientific
digital archives containing images of specimens. Unfortunately, metadata errors can inhibit …

Computational archival science (CAS) provides new pathways for research. Biologists, for
example, can perform scientific studies by applying AI/ML to digital biological specimen …

This study evaluates the performance of four image recognition tools (Amazon Rekognition,
Clarifai, Imagga and Google Cloud Vision API) for automatic image metadata. The …

A new science discipline has emerged within the last decade at the intersection of
informatics, computer science and biology: Imageomics. Like most other-omics fields …

Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the
study of evolutionary morphology. While classical AI methods such as principal component …