{"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":"

A compilation of research being done at Microsoft on accelerating biodiversity surveys with AI<\/h2>\n

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

Code<\/h3>\n