{"id":7386,"date":"2020-08-25T11:04:14","date_gmt":"2020-08-25T16:04:14","guid":{"rendered":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/?p=7386"},"modified":"2026-02-18T11:29:54","modified_gmt":"2026-02-18T16:29:54","slug":"mil-cam-accepted-to-eccv-2020","status":"publish","type":"post","link":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/2020\/08\/25\/mil-cam-accepted-to-eccv-2020\/","title":{"rendered":"MIL-CAM ACCEPTED TO ECCV 2020 WORKSHOP ON COMPUTER VISION PROBLEMS IN PLANT PHENOTYPING!"},"content":{"rendered":"<figure id=\"attachment_7400\" aria-describedby=\"caption-attachment-7400\" style=\"width: 1427px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-7400 size-full\" src=\"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-content\/uploads\/sites\/759\/2020\/08\/mil_cam.png\" alt=\"\" width=\"1427\" height=\"520\" srcset=\"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-content\/uploads\/sites\/759\/2020\/08\/mil_cam.png 1427w, https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-content\/uploads\/sites\/759\/2020\/08\/mil_cam-300x109.png 300w, https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-content\/uploads\/sites\/759\/2020\/08\/mil_cam-1024x373.png 1024w, https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-content\/uploads\/sites\/759\/2020\/08\/mil_cam-768x280.png 768w\" sizes=\"auto, (max-width: 1427px) 100vw, 1427px\" \/><figcaption id=\"caption-attachment-7400\" class=\"wp-caption-text\">Diagram of the MIL-CAM model for minirhizotron root segmentation.<\/figcaption><\/figure>\n<p>Congratulations to our labmates and collaborators: <strong>Guohao Yu, Alina Zare, Weihuang Xu<\/strong>, Roser Matamala, Joel Reyes-Cabrera, Felix B. Fritschi and Thomas E. Juenger!\u00a0 Their paper,<strong> &#8220;Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM&#8221;<\/strong> was recently accepted to the <em>16th European Conference on Computer Vision (ECCV) Workshop on Computer Vision Problems in Plant Phenotyping (CVPPP 2020).<\/em>\u00a0\u00a0<\/p>\n<p>Their paper explores weakly supervised minirhizotron image segmentation as way to ease tedious labeling tasks for root segmentation.\u00a0 The authors introduce a multiple instance class activation map (MIL-CAM) which learns from image-level labels to perform pixel-level segmentation.\u00a0 Results show that the proposed method outperforms alternative methods for localization of root objects in minrhizotron imagery.<\/p>\n<p>Guohao will present for the virtual conference on <strong>August 28th.<\/strong>\u00a0 Check out the pre-print <a href=\"https:\/\/faculty.eng.ufl.edu\/machine-learning\/2020\/08\/weakly-supervised-minirhizotron-image-segmentation-with-mil-cam\">here!<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Congratulations to our labmates and collaborators: Guohao Yu, Alina Zare, Weihuang Xu, Roser Matamala, Joel Reyes-Cabrera, Felix B. Fritschi and Thomas E. Juenger!\u00a0 Their paper, &#8220;Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM&#8221; was recently accepted to the 16th European Conference on Computer Vision (ECCV) Workshop on Computer Vision Problems in Plant Phenotyping (CVPPP 2020).\u00a0\u00a0 Their [&hellip;]<\/p>\n","protected":false},"author":28,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-templates\/single-sidebar-none.php","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[17,9],"tags":[149,465,487,639,659],"class_list":["post-7386","post","type-post","status-publish","format-standard","hentry","category-conference_paper","category-news","tag-class-activation-map","tag-minirhizotron","tag-multiple-instance","tag-roots","tag-segmentation"],"acf":[],"_links":{"self":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts\/7386","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/users\/28"}],"replies":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/comments?post=7386"}],"version-history":[{"count":1,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts\/7386\/revisions"}],"predecessor-version":[{"id":15239,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts\/7386\/revisions\/15239"}],"wp:attachment":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/media?parent=7386"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/categories?post=7386"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/tags?post=7386"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}