{"id":825934,"date":"2022-03-18T14:51:59","date_gmt":"2022-03-18T21:51:59","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-blog-post&p=825934"},"modified":"2022-03-21T13:11:27","modified_gmt":"2022-03-21T20:11:27","slug":"biodiversity-surveys-research-compilation","status":"publish","type":"msr-blog-post","link":"https:\/\/www.microsoft.com\/en-us\/research\/articles\/biodiversity-surveys-research-compilation\/","title":{"rendered":"Biodiversity surveys research compilation"},"content":{"rendered":"
We apply machine learning tools to a variety of image sources \u2013 including motion-triggered camera traps, aerial cameras, and microphones \u2013 to accelerate ecologists\u2019 workflows. Our team spans Microsoft Research,\u00a0Microsoft AI for Earth (opens in new tab)<\/span><\/a>, and the\u00a0AI for Good Research Lab (opens in new tab)<\/span><\/a>.<\/p>\n (opens in new tab)<\/span><\/a><\/p>\n (opens in new tab)<\/span><\/a><\/p>\n Whoever \u201cwe\u201d are (i.e., the \u201cwe\u201d who maintain this page), \u201cwe\u201d are not the only ones at Microsoft working in this area. Here are some other great projects that our Microsoft colleagues have worked on in the biodiversity space:<\/p>\n A compilation of research being done at Microsoft on accelerating biodiversity surveys with AI We apply machine learning tools to a variety of image sources \u2013 including motion-triggered camera traps, aerial cameras, and microphones \u2013 to accelerate ecologists\u2019 workflows. Our team spans Microsoft Research,\u00a0Microsoft AI for Earth, and the\u00a0AI for Good Research Lab. Code Accelerating […]<\/p>\n","protected":false},"author":40306,"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-content-parent":597754,"footnotes":""},"research-area":[],"msr-locale":[268875],"msr-post-option":[],"class_list":["post-825934","msr-blog-post","type-msr-blog-post","status-publish","hentry","msr-locale-en_us"],"msr_assoc_parent":{"id":597754,"type":"project"},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/825934"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-blog-post"}],"author":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/users\/40306"}],"version-history":[{"count":7,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/825934\/revisions"}],"predecessor-version":[{"id":828889,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/825934\/revisions\/828889"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=825934"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=825934"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=825934"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=825934"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Code<\/h3>\n
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Data<\/h3>\n
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Demos<\/h3>\n
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APIs<\/h3>\n
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Publications and publication-like things<\/h3>\n
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Blogs and blog-like things<\/h3>\n
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Other work at Microsoft<\/h3>\n
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Literature reviews<\/h3>\n
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