{"id":2074,"date":"2024-08-09T14:38:12","date_gmt":"2024-08-09T13:38:12","guid":{"rendered":"https:\/\/www.sfpt.fr\/hyperspectral\/?p=2074"},"modified":"2024-08-09T14:38:12","modified_gmt":"2024-08-09T13:38:12","slug":"conference-deeplearning3d-classification-of-hyperspectrales-3d-data-with-machine-learning","status":"publish","type":"post","link":"https:\/\/www.sfpt.fr\/hyperspectral\/?p=2074","title":{"rendered":"Conf\u00e9rence : deeplearning3d : Classification of hyperspectrales 3D data with machine-learning"},"content":{"rendered":"\n
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We are excited to announce the upcoming <\/span>Deep Learning for 3D Conference<\/b><\/span>. This event will bring together leading researchers, industry professionals, students and postdocs to explore the <\/span>latest advancements and applications of deep learning applied on 3D hyperspectral data<\/strong>. <\/span><\/div>\n
This workshop will be a unique opportunity to connect with peers, form collaborations, and exchange ideas on 3D classification techniques. In particular, we aim to bring experts in ML and users of 3D hyperspectral data in order to exchange ideas around 3D ML techniques \u00a0such as un\/supervised classification, 3D deblending, 3D segmentation and inverse problems. <\/span><\/div>\n
We particularly encourage contributions from young researchers in France or with ties to the French community to present their work.<\/span><\/div>\n
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Location: <\/b><\/span>ENS Lyon<\/span><\/div>\n
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Date: <\/b><\/span>Nov 14-15, 2024<\/span><\/div>\n
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Submission deadline: <\/b><\/span>Sep 15, 2024<\/span><\/div>\n
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For detailed submission guidelines, please visit the practical information on our <\/span>conference website<\/a><\/span>.<\/span><\/div>\n

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\u00a0 We are excited to announce the upcoming Deep Learning for 3D Conference. This event will bring together leading researchers, industry professionals, students and postdocs to explore the latest advancements and applications of deep learning applied on 3D hyperspectral data. This workshop will be a unique opportunity to connect with peers, form collaborations, and exchange … <\/p>\n

Continuer la lecture de « Conf\u00e9rence : deeplearning3d : Classification of hyperspectrales 3D data with machine-learning »<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_s2mail":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-2074","post","type-post","status-publish","format-standard","hentry","category-non-classe"],"_links":{"self":[{"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=\/wp\/v2\/posts\/2074","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2074"}],"version-history":[{"count":1,"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=\/wp\/v2\/posts\/2074\/revisions"}],"predecessor-version":[{"id":2075,"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=\/wp\/v2\/posts\/2074\/revisions\/2075"}],"wp:attachment":[{"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2074"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2074"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.sfpt.fr\/hyperspectral\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2074"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}