The Digital Collectomics group applies the latest advancements in computer vision and AI to automate the analysis of preserved specimens from herbaria and beyond. These methods enable the thorough investigation of vast herbarium collections, extracting species, trait, and metadata from millions of specimens with minimal manual effort. By leveraging historical archives, we can map these data points across broad spatio-temporal scales, investigate the impacts of environmental change at scale, and elevate collection-based research to unprecedented levels.
Currently, our research focuses on automating the extraction of phenological data from herbarium specimens and transcribing handwritten historical herbarium labels, with additional projects in development.
