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AI-driven advances in Species Identification and Biomass Analysis

Shirali, Hossein ORCID iD icon 1; Wuhrl, Lorenz ORCID iD icon 1; Klug, Nathalie 1
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

Abstract:

Artificial Intelligence (AI) is reshaping our understanding of the natural world, bringing transformative changes to entomology and biodiversity studies. The emergence of user-friendly AI-driven applications, recognizable in daily life through tools that identify various species from images or sounds, marks a new era in entomological research. These advancements facilitate citizen scientists' and professionals' research by simplifying species identification. However, the potential of AI extends far beyond the familiar terrains of the global North, where it has predominantly been utilized due to earlier access to advanced technologies.
In this presentation, we delve into how AI, synergized with innovative and cost-effective technologies like DIY microscopes, is breaking barriers in biodiversity research, especially in resource-limited settings. This novel approach empowers researchers to assess species diversity, abundance, and biomass efficiently, offering faster and more cost-effective ways to understand ecological patterns and change. We have advanced these efforts by applying AI to image-based biomass estimation of invertebrates. ... mehr

Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Vortrag
Publikationsdatum 18.03.2025
Sprache Englisch
Identifikator KITopen-ID: 1000180291
Veranstaltung Entomology Congress (DGaaE 2025), Geisenheim, Deutschland, 17.03.2025 – 20.03.2025
Schlagwörter Artificial Intelligence (AI), Machine Learning, Deep Learning, Species Identification, Biomass Estimation
Referent/Betreuer Meier, Rudolf
Pylatiuk, Christian

Volltext §
DOI: 10.5445/IR/1000180291
Veröffentlicht am 21.03.2025
Seitenaufrufe: 27
seit 21.03.2025
Downloads: 6
seit 22.03.2025
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