Romero, I.C., Department of Plant Biology, University of Illinois at Urbana–Champaign, Urbana, IL 61801, United States; Kong, S., Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, United States, Department of Computer Science, University of California, Irvine, CA 92697, United States; Fowlkes, C.C., Department of Computer Science, University of California, Irvine, CA 92697, United States; Jaramillo, C., Center for Tropical Paleoecology and Archaeology, Smithsonian Tropical Research Institute, Ancon, 0843-03092, Panama, Institut des Sciences de l’Évolution de Montpellier, Université de Montpellier, CNRS, Ecole Pratique des Hautes Études, Institut de Recherche pour le Développement, Montpellier, 34095, France, Department of Geology, Faculty of Sciences, University of Salamanca, Salamanca, 37008, Spain; Urban, M.A., Department of Plant Biology, University of Illinois at Urbana–Champaign, Urbana, IL 61801, United States, Department of Biology, University of New Brunswick, Fredericton, NB E3B 5A3, Canada; Oboh-Ikuenobe, F., Department of Geosciences and Geological and Petroleum Engineering, Missouri University of Science and Technology, Rolla, MO 65409, United States; D’Apolito, C., Faculdade de Geociencias, Universidade Federal de Mato Grosso, Cuiaba, 78000, Brazil; Punyasena, S.W., Department of Plant Biology, University of Illinois at Urbana–Champaign, Urbana, IL 61801, United States
Recommended Citation:
Romero I.C.,Kong S.,Fowlkes C.C.,et al. Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy[J]. Proceedings of the National Academy of Sciences of the United States of America,2020-01-01,117(45)