專題報告:海洋生物聲學的探測與分類與深度學習（CS SD）
- 2020 年 3 月 17 日
- 筆記
019年11月21-22日，約30名研究人員齊聚加拿大BC省維多利亞州，參加由子午線組織、加拿大海洋網主辦的「海洋生物聲學深度學習檢測與分類」研討會。出席了研討會海洋生物學家、數據科學家,和電腦科學家來自加拿大海岸和美國和代表廣泛的研究機構,包括大學、政府(加拿大漁業和海洋,國家海洋和大氣管理局)、行業(JASCO應用科學,Google,Axiom數據科學),和非營利性(Orcasound OrcaLab)。該研討會由口頭報告、公開討論和實踐教程組成，為來自不同領域的專家提供了一個難得的機會，讓他們參與到關於深度學習及其在水聲探測和分類演算法發展中的潛力的討論中。在這個專題報告中，我們總結了演講和討論的要點。
原文題目：Workshop Report: Detection and Classification in Marine Bioacoustics with Deep Learning
原文：On 21-22 November 2019, about 30 researchers gathered in Victoria, BC, Canada, for the workshop "Detection and Classification in Marine Bioacoustics with Deep Learning" organized by MERIDIAN and hosted by Ocean Networks Canada. The workshop was attended by marine biologists, data scientists, and computer scientists coming from both Canadian coasts and the US and representing a wide spectrum of research organizations including universities, government (Fisheries and Oceans Canada, National Oceanic and Atmospheric Administration), industry (JASCO Applied Sciences, Google, Axiom Data Science), and non-for-profits (Orcasound, OrcaLab). Consisting of a mix of oral presentations, open discussion sessions, and hands-on tutorials, the workshop program offered a rare opportunity for specialists from distinctly different domains to engage in conversation about deep learning and its promising potential for the development of detection and classification algorithms in underwater acoustics. In this workshop report, we summarize key points from the presentations and discussion sessions.
原文作者：Fabio Frazao, Bruno Padovese, Oliver S. Kirsebom
原文地址：http://cn.arxiv.org/abs/2002.08249
