首页|Machine learning outcompetes human assessment in identifying eggs of a conspecif ic brood parasite
Machine learning outcompetes human assessment in identifying eggs of a conspecif ic brood parasite
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from bi orxiv.org:“Avian brood parasitism provides an exceptional system for studying coevolution. While conspecificbrood parasitism (CBP) is more common than interspecific para sitism, it is less studied due to the challengeof detecting parasitic eggs, whi ch closely resemble those of the host. Although molecular genotyping canaccurat ely detect CBP, its high cost has led researchers to explore egg appearance as a more accessiblealternative. Barn swallows (Hirundo rustica) are considered con specific brood parasites, but identifyingparasitic eggs has traditionally relie d on human visual assessment. Here, we used UV-visible photographsof non-parasi tized barn swallow clutches and simulated parasitism to compare the accuracy of humanassessment with automated methods.
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