{"id":4785,"date":"2023-08-20T21:39:21","date_gmt":"2023-08-21T01:39:21","guid":{"rendered":"https:\/\/web.uri.edu\/oeci\/?page_id=4785"},"modified":"2023-11-05T20:03:08","modified_gmt":"2023-11-06T01:03:08","slug":"projects-machine-learning-video","status":"publish","type":"page","link":"https:\/\/web.uri.edu\/oeci\/about\/oeci-projects-main-page\/projects-machine-learning-video\/","title":{"rendered":"Projects &#8211; Machine Learning Video"},"content":{"rendered":"\n<div class=\"wp-block-cover has-background-dim\"><img loading=\"lazy\" decoding=\"async\" width=\"750\" height=\"422\" class=\"wp-block-cover__image-background wp-image-4897\" alt=\"\" src=\"https:\/\/web.uri.edu\/oeci\/wp-content\/uploads\/sites\/1967\/raman-invader.jpg\" data-object-fit=\"cover\" srcset=\"https:\/\/web.uri.edu\/oeci\/wp-content\/uploads\/sites\/1967\/raman-invader.jpg 750w, https:\/\/web.uri.edu\/oeci\/wp-content\/uploads\/sites\/1967\/raman-invader-300x169.jpg 300w, https:\/\/web.uri.edu\/oeci\/wp-content\/uploads\/sites\/1967\/raman-invader-150x84.jpg 150w, https:\/\/web.uri.edu\/oeci\/wp-content\/uploads\/sites\/1967\/raman-invader-364x205.jpg 364w, https:\/\/web.uri.edu\/oeci\/wp-content\/uploads\/sites\/1967\/raman-invader-500x281.jpg 500w\" sizes=\"auto, (max-width: 750px) 100vw, 750px\" \/><div class=\"wp-block-cover__inner-container is-layout-flow wp-block-cover-is-layout-flow\">\n<p class=\"has-text-align-center has-large-font-size\">Machine Learning Video<\/p>\n\n\n\n<p class=\"has-text-align-center\">Adam Soule (URI)<\/p>\n<\/div><\/div>\n\n\n\n<h6 class=\"wp-block-heading\">Photo by <a href=\"https:\/\/www.impossiblesensing.com\/post\/impossible-sensing-brings-high-tech-laser-lab-to-the-ocean-floor\">OET<\/a><\/h6>\n\n\n\n<hr class=\"wp-block-separator\" \/>\n\n\n\n<h2 class=\"wp-block-heading\">Overview<\/h2>\n\n\n\n<p>Deep-sea video is one of the most important data sources in deep-sea science, but also an extreme challenge for data usage and archiving due to the very large data volumes produced. For general use, underwater dive videos can be sparse, with only a few high-value clips interspersed with hours of video relevant only to specific domains. The process of condensing such high-volume data can be time-consuming as human annotators must manually clip videos to identify highlights. To help, OECI-supported researchers and graduate students developed ROVIA, a portable and field-deployable CNN (Convolutional Neural Network) model to identify potential biological, geological, and operational highlights from long-dive videos. This automated video highlight generator provides increased efficiency in condensing deep-sea video to aid in archiving and enhance the utilization of clips for scientific and educational purposes.<\/p>\n\n\n<section class=\"cl-wrapper cl-boxout-wrapper\"><div class=\"cl-boxout  \"><h1>This project is available on GitHub<\/h1>\n<a class=\"cl-button  \" href=\"https:\/\/github.com\/oeci\/ROVIA\" title=\"\">view repository<\/a>\n<\/div><\/section>\n\n\n<p> <\/p>\n\n\n\n<hr class=\"wp-block-separator\" \/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:28%\"><\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\"><a class=\"cl-button  \" href=\"https:\/\/web.uri.edu\/oeci\/oeci-projects-main-page\/\" title=\"\">return to projects directory<\/a><\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:28%\"><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Photo by OET Overview Deep-sea video is one of the most important data sources in deep-sea science, but also an extreme challenge for data usage and archiving due to the very large data volumes produced. For general use, underwater dive videos can be sparse, with only a few high-value clips interspersed with hours of video [&hellip;]<\/p>\n","protected":false},"author":4819,"featured_media":0,"parent":4328,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-4785","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/pages\/4785","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/users\/4819"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/comments?post=4785"}],"version-history":[{"count":5,"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/pages\/4785\/revisions"}],"predecessor-version":[{"id":5497,"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/pages\/4785\/revisions\/5497"}],"up":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/pages\/4328"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/oeci\/wp-json\/wp\/v2\/media?parent=4785"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}