Classifying and Indexing

October 28, 2021 / Melody Smith / Comments Off on Classifying and Indexing

A team of scientists in Austria has created a new artificial intelligence (AI) program to speed up their research. It automatizes the analysis of huge numbers of plant images. JStor Daily brought this interesting topic to our attention in their article, “Botanists Use Machine Learning to Accelerate Research.”

The study of plants involves identifying both their genotype and their phenotype. Accessing the genomic sequence of an organism is a fundamental part of the study of biology. Doing this faster and with better accuracy allows researchers to make connections between a certain phenotype, such as height or color, and the genes responsible for it.

ARADEEPOPSIS uses semantic segmentation of top-view images to classify leaf tissue into three categories: healthy, anthocyanin rich and senescent. ARADEEPOPSIS is deployable on most operating systems and high-performance computing environments and can be used independently of bioinformatics expertise and resources.

A controlled vocabulary is needed to ensure that the machine-assisted or fully automated indexing is comprehensive, regardless of what you are indexing. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies to make their information findable.

Melody K. Smith

Sponsored by Access Innovations, changing search to found.

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Melody Smith

Melody K. Smith has provided organizational, social media and digital communication services to a large non-profit for the past twenty years. Prior to that she championed employee engagement and communications in the healthcare field. She holds a Bachelors degree in Marketing. When not wrangling and writing TaxoDiary content for your reading pleasure, Melody writes fiction, rescues dogs and throws legendary dinner parties.