{"refrec":{"BRefID":361885,"RR":"<b>Orenstein, E.C.; Ayata, S.-D.; Maps, F.; Becker, E.C.; Benedetti, F.; Biard, T.; de Garidel-Thoron, T.; Ellen, J.S.; Ferrario, F.; Giering, S.L.C.; Guy-Haim, T.; Hoebeke, L.; Iversen, M.H.; Kiørboe, T.; Lalonde, J.-F.; Lana, A.; Laviale, M.; Lombard, F.; Lorimer, T.; Martini, S.; Meyer, A.; Möller, K.O.; Niehoff, B.; Ohman, M.D.; Pradalier, C.; Romagnan, J.-B.; Schröder, S.-M.; Sonnet, V.; Sosik, H.M.; Stemmann, L.S.; Stock, M.; Terbiyik Kurt, T.; Valcárcel-Pérez, N.; Vilgrain, L.; Wacquet, G.; Waite, A.M.; Irisson, J.-O.</b> (2022). Machine learning techniques to characterize functional traits of plankton from image data. <i>Limnol. Oceanogr. 67(8)</i>: 1647-1669. <a href=\"https://dx.doi.org/10.1002/lno.12101\" target=\"_blank\">https://dx.doi.org/10.1002/lno.12101</a>","BEntID":359601,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":0,"RefStringPartII":". <i>Limnol. Oceanogr. 67(8)</i>: 1647-1669. <a href=\"https://dx.doi.org/10.1002/lno.12101\" target=\"_blank\">https://dx.doi.org/10.1002/lno.12101</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Orenstein, E.C.; Ayata, S.-D.; Maps, F.; Becker, E.C.; Benedetti, F.; Biard, T.; de Garidel-Thoron, T.; Ellen, J.S.; Ferrario, F.; Giering, S.L.C.; Guy-Haim, T.; Hoebeke, L.; Iversen, M.H.; Kiørboe, T.; Lalonde, J.-F.; Lana, A.; Laviale, M.; Lombard, F.; Lorimer, T.; Martini, S.; Meyer, A.; Möller, K.O.; Niehoff, B.; Ohman, M.D.; Pradalier, C.; Romagnan, J.-B.; Schröder, S.-M.; Sonnet, V.; Sosik, H.M.; Stemmann, L.S.; Stock, M.; Terbiyik Kurt, T.; Valcárcel-Pérez, N.; Vilgrain, L.; Wacquet, G.; Waite, A.M.; Irisson, J.-O.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Orenstein, E.C. <i>et al.</i>","Englishabstract":"Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. 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