没有合适的资源?快使用搜索试试~ 我知道了~
海洋数据和人工智能用于物种保护(英).pdf
1.该资源内容由用户上传,如若侵权请联系客服进行举报
2.虚拟产品一经售出概不退款(资源遇到问题,请及时私信上传者)
2.虚拟产品一经售出概不退款(资源遇到问题,请及时私信上传者)
版权申诉
0 下载量 194 浏览量
2022-11-16
15:47:08
上传
评论
收藏 4.31MB PDF 举报
温馨提示
![preview](https://dl-preview.csdnimg.cn/87033544/0001-a2fe70ff5811b53d835918c7cc2983fb_thumbnail.jpeg)
![preview-icon](https://csdnimg.cn/release/downloadcmsfe/public/img/scale.ab9e0183.png)
试读
14页
海洋数据和人工智能用于物种保护(英).pdf
资源推荐
资源详情
资源评论
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![](https://csdnimg.cn/release/download_crawler_static/87033544/bg1.jpg)
Ocean Data
and AI for
species
conservation
1
![](https://csdnimg.cn/release/download_crawler_static/87033544/bg2.jpg)
The problem and at the same time our
motivation is the loss of species diversity in the
ocean, which is often also referred to as ”invisible
dying”. With our approach, we pursue the goal of
making this dying visible and thus preventable.
To make events in the ocean visible, we need
to identify patterns depending on the ocean
depth and then recognize deviations from these
patterns. With the Norwegian institute Lofoten-
Vesteralen, we are analyzing ocean data, to help
detect anomalies. This should enable a better
understanding of the ocean ecosystem. This
should help to identify the consequences of
human intervention in nature, such as dwindling
sh stocks.
Abstract.
2OCEAN DATA AND AI FOR SPECIES CONSERVATION I OCTOBER 2022
![](https://csdnimg.cn/release/download_crawler_static/87033544/bg3.jpg)
Accurate observation of ecosystems enable
detailed oceanographic research, allowing
anomalies to be identied in enormous
amounts of data with the help of articial
intelligence (AI).
The Lofoten-Vester˚alen (LoVe) Ocean Observatory is located
west of Hovden Vester˚alen in the northern part of Norway.
It is located in an ecological, geological, oceanographic and
economic ”hotspot”. A network of submarine cables and
seven sensor nodes covers a cross-section from the mainland
to the deep sea. It includes a land-based station and seven
sensor platforms, covering a gradient from sea level to a
depth of 200m. The system continuously provides valuable
online data on the marine environment in northern Norway,
and has been active since 2013.
The system is both, a national research infrastructure,
basic and applied research, as well as a test infrastructure,
where industry partners can test new underwater
sensors and technologies. The Lofoten-Vester˚alen Ocean
Observatory has collected over 100 terabytes of sensor data
(temperatures, currents, echograms) over the years.
Thomas Ramm
is a Software Engineer at Capgemini.
He created the initial infrastructure and
GitHub integration.
Nils Olav Handegaard
is a researcher at the LoVe Ocean Observatory.
His research focuses on the application of new
methodologies and data processing techniques
to the elds of marine ecology and sheries
oceanography.
Majed Alaitwni
is a software developer. The focus of
his bachelor thesis was interactive
visualization for anomaly detection in
ocean measurement data. He
created the visualization.
Daniel Friedmann
is a software developer at Capgemini. He is
an expert in containerization and Docker and
provides content support for the project.
Sophie Bader
is a molecular biologist specializing in oceanic
ecosystems, as well as a software developer.
She assisted with the infrastructure.
Geir Pedersen
is a researcher at the LoVeOcean Ocean
Observatory and supports the project on
the Norwegian side.
parMustapha Mustapha
is a software developer at Capgemini. He has
done planning work and helped design the
original AI model.
Eldar Sultanow is Enterprise Architect Director at Capgemini. His main focus is on modern
software architectures, digitalization and enterprise architecture management. He developed the
code with Thomas Ramm in the initial phase and is now supervisor of the project and oversees
research work.
Tom Hatton
is a Data Scientist, his master’s thesis
explored the use of unsupervised AI
models for anomaly detection in high-
dimensional ocean measurement data. He
continues to develop the AI model.
3
Introduction
The team
OCEAN DATA AND AI FOR SPECIES CONSERVATION I OCTOBER 2022
剩余13页未读,继续阅读
资源评论
![avatar-default](https://csdnimg.cn/release/downloadcmsfe/public/img/lazyLogo2.1882d7f4.png)
![avatar](https://profile-avatar.csdnimg.cn/default.jpg!1)
如此醉123
- 粉丝: 231
- 资源: 9万+
上传资源 快速赚钱
我的内容管理 展开
我的资源 快来上传第一个资源
我的收益
登录查看自己的收益我的积分 登录查看自己的积分
我的C币 登录后查看C币余额
我的收藏
我的下载
下载帮助
![voice](https://csdnimg.cn/release/downloadcmsfe/public/img/voice.245cc511.png)
![center-task](https://csdnimg.cn/release/downloadcmsfe/public/img/center-task.c2eda91a.png)
安全验证
文档复制为VIP权益,开通VIP直接复制
![dialog-icon](https://csdnimg.cn/release/downloadcmsfe/public/img/green-success.6a4acb44.png)