Titlebook: Advances in Visual Computing; 17th International S George Bebis,Bo Li,Remco Chang Conference proceedings 2022 The Editor(s) (if applicable)

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Conservation of Threatened Plants need for automated systems that can detect and classify invasive and non-invasive aquatic species using underwater videos without human supervision. In this paper, we intend to classify the larvae of invasive species like Zebra and Quagga mussels. These organisms are native to eastern Europe, but a

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The Records System of Uppsala Botanic Garden existing recognition methods focus on individual datasets with a known set of classes limiting their wider applicability. Automated plankton imaging instruments capture images of unknown particles and the class (plankton species) composition varies between geographical regions and ecosystems. This

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Conservation of Threatened Plantsier and dataset. Such existing formulations employ a learned rejection (remove)/selection (keep) function and require either a known cost for rejecting examples or strong constraints on the accuracy or coverage of the . examples. We consider an alternative formulation by instead analyzing the comple

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Advances in Visual Computing978-3-031-20713-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

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