Machine learning algorithms have successfully identified plant species in massive herbaria just by looking at the dried specimens. According to researchers, similar AI approaches could also be used identify the likes of fly larvae and plant fossils. From Nature:
There are roughly 3,000 herbaria in the world, hosting an estimated 350 million specimens — only a fraction of which has been digitized. But the swelling data sets, along with advances in computing techniques, enticed computer scientist Erick Mata-Montero of the Costa Rica Institute of Technology in Cartago and botanist Pierre Bonnet of the French Agricultural Research Centre for International Development in Montpellier, to see what they could make of the data.
Researchers trained... algorithms on more than 260,000 scans of herbarium sheets, encompassing more than 1,000 species. The computer program eventually identified species with nearly 80% accuracy: the correct answer was within the algorithms’ top 5 picks 90% of the time. That, says (Penn State paleobotanist Peter) Wilf, probably out-performs a human taxonomist by quite a bit.
Such results often worry botanists, Bonnet says, many of whom already feel that their field is undervalued. “People feel this kind of technology could be something that will decrease the value of botanical expertise,” he says. “But this approach is only possible because it is based on the human expertise. It will never remove the human expertise.” People would also still need to verify the results, he adds.
"Going deeper in the automated identification of Herbarium specimens" (BMC Evolutionary Biology)
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