{"id":71,"date":"2022-05-23T16:52:27","date_gmt":"2022-05-23T14:52:27","guid":{"rendered":"https:\/\/rapmed.osupytheas.fr\/?page_id=71"},"modified":"2023-06-28T09:52:05","modified_gmt":"2023-06-28T07:52:05","slug":"communications","status":"publish","type":"page","link":"https:\/\/rapmed.osupytheas.fr\/?page_id=71","title":{"rendered":"Communications"},"content":{"rendered":"\n
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Plankton image classification using convolutional neural networks ; Thang Duong Quoc Le, David N\u00e9rini, Cristele Chevalier, Ross Marchant, and Thibault De Garidel-Thoron<\/em>  ; olloque  Ecostat 2021: R\u00e9union annuelle du GDR Ecologie Statistique<\/a>  (8 et 9 avril 2021) ;\nPlankton microorganisms are among the most important players in marine ecosystems. Studying the changes in plankton communities under environmental perturbations is essential to better understand the effects of environmental changes to marine ecosystems. Large image datasets of plankton acquired by emerging imaging devices (e.g., FlowCam and Zooscan) have the potential to document plankton dynamics. In our work, we investigate such changes using deep learning methods, such as convolutional neural networks (CNNs), for image classification, testing different CNN architectures. To evaluate the performance of CNN classifiers, we study the influences of different hyperparameters such as number of hidden layers and units, network weight initialization, learning rate, number of epochs and batch size. Then, we will discuss the performance of CNN classifiers with other feature-based classification methods such as Support Vector Machine and Fast Random Forest.<\/pre>\n<\/div><\/div>\n\n\n\n
Variabilit\u00e9 du m\u00e9sozooplancton dans la baie de Marseille (M\u00e9diterran\u00e9e Nord-occidentale) : vers la compr\u00e9hension du contexte trophique des petits p\u00e9lagiques. Th\u00e9o GARCIA, Daniela B\u0102NARU, Lo\u00efc GUILLOUX, V\u00e9ronique CORNET, G\u00e9rald GREGORI, Fran\u00e7ois CARLOTTI. (Pr\u00e9sentation orale). Journ\u00e9e d’Inter-comparaison SOMLIT. 2022<\/a>. Marseille<\/p>\n\n\n\n
Mesozooplankton variability in the Bay of Marseille (NW Mediterranean): towards understanding the trophic context of small pelagics. GARCIA Th\u00e9o, B\u0102NARU Daniela, GUILLOUX Lo\u00efc, CORNET V\u00e9ronique, GREGORI G\u00e9rald, PERAUD Manon, CARLOTTI Fran\u00e7ois. (Oral presentation). SIBECOL Aveiro<\/a> 2022 .<\/p>\n\n\n\n
Mesozooplankton interannual variability in the Bay of Marseille (NW-Mediterranean Sea): towards understanding trophic context of small pelagic fish. GARCIA Th\u00e9o, B\u0102NARU Daniela, GUILLOUX Lo\u00efc, CORNET V\u00e9ronique, GREGORI G\u00e9rald, PERAUD Manon, CARLOTTI Fran\u00e7ois. (Poster) Congr\u00e8s des doctorants 2022<\/a>. Marseille<\/p>\n\n\n\n
Mesozooplankton interannual variability in the Bay of Marseille (NW-Mediterranean Sea): towards understanding trophic context of small pelagic fish. GARCIA Th\u00e9o, B\u0102NARU Daniela, GUILLOUX Lo\u00efc, CORNET V\u00e9ronique, GREGORI G\u00e9rald, PERAUD Manon, CARLOTTI Fran\u00e7ois. (Poster) 8e Rencontre de l’Icthyologie en France<\/a>. Paris 2022. <\/p>\n\n\n\n
Exemple de l\u2019utilisation de ParticleTrieur pour l\u2019analyse de s\u00e9ries temporelles du zooplancton de la baie de Marseille (SOMLIT). Garcia T., B\u0103naru D., Guilloux L., Peraud M., Carlotti F. (Pr\u00e9sentation orale). Journ\u00e9es de l’OSU Institut Pyth\u00e9as<\/span>. Aix en Provence 2022.<\/p>\n\n\n\n
Tendances environnementales et variabilit\u00e9 interannuelle du zooplancton en baie de  Marseille (NO M\u00e9diterran\u00e9e). Garcia T., B\u0103naru D., Cornet V., Guilloux L., Peraud M., Carlotti F. (Pr\u00e9sentation orale). Congr\u00e8s ILICO EVOLECO<\/a>. La Rochelle 2021.<\/p>\n\n\n\n
Automatic classification of benthic foraminifera for biomonitoring studies. Tobias Walla, Christine Barras, Emmanuelle Geslin, Louis Lanoy, Jean-Charles Mazur, Camille Godbillot, Ross Marchant, Thibault de Garidel-Thoron ; GeoBerlin 2023<\/a> ; septembre 2023.
<\/p>\n","protected":false},"excerpt":{"rendered":"
Plankton image classification using convolutional neural networks ; Thang Duong Quoc Le, David N\u00e9rini, Cristele Chevalier, Ross Marchant, and Thibault De Garidel-Thoron ; olloque  Ecostat 2021: R\u00e9union annuelle du GDR Ecologie Statistique (8 et 9 avril 2021) ; Plankton microorganisms are among the most important players in marine ecosystems. Studying the changes in plankton communities … <\/p>\n
Continuer la lecture de « Communications »<\/span><\/a><\/p>\n","protected":false},"author":6,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-71","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=\/wp\/v2\/pages\/71","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=71"}],"version-history":[{"count":8,"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=\/wp\/v2\/pages\/71\/revisions"}],"predecessor-version":[{"id":108,"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=\/wp\/v2\/pages\/71\/revisions\/108"}],"wp:attachment":[{"href":"https:\/\/rapmed.osupytheas.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=71"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}