Artwork

Indhold leveret af HackerNoon. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af HackerNoon eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Player FM - Podcast-app
Gå offline med appen Player FM !

Real-Time Anomaly Detection in Underwater Gliders: Experimental Evaluation

10:13
 
Del
 

Manage episode 419839917 series 3474670
Indhold leveret af HackerNoon. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af HackerNoon eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/real-time-anomaly-detection-in-underwater-gliders-experimental-evaluation.
This paper presents a real-time anomaly detection algorithm to enhance underwater glider safety using datasets from actual deployments.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-analysis, #machine-learning, #underwater-gliders, #anomaly-detection, #oceanography, #glider-navigation, #ocean-data, #marine-robotics, and more.
This story was written by: @oceanography. Learn more about this writer by checking @oceanography's about page, and for more stories, please visit hackernoon.com.
We apply the anomaly detection algorithm to four glider deployments across the coastal ocean of Florida and Georgia, USA. For evaluation, the anomaly detected by the algorithm is cross-validated by high-resolution glider DBD data and pilot notes. We simulate the online detection process on SBD and compare the result with that detected from DBD.

  continue reading

150 episoder

Artwork
iconDel
 
Manage episode 419839917 series 3474670
Indhold leveret af HackerNoon. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af HackerNoon eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/real-time-anomaly-detection-in-underwater-gliders-experimental-evaluation.
This paper presents a real-time anomaly detection algorithm to enhance underwater glider safety using datasets from actual deployments.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-analysis, #machine-learning, #underwater-gliders, #anomaly-detection, #oceanography, #glider-navigation, #ocean-data, #marine-robotics, and more.
This story was written by: @oceanography. Learn more about this writer by checking @oceanography's about page, and for more stories, please visit hackernoon.com.
We apply the anomaly detection algorithm to four glider deployments across the coastal ocean of Florida and Georgia, USA. For evaluation, the anomaly detected by the algorithm is cross-validated by high-resolution glider DBD data and pilot notes. We simulate the online detection process on SBD and compare the result with that detected from DBD.

  continue reading

150 episoder

Alle episoder

×
 
Loading …

Velkommen til Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Hurtig referencevejledning

Lyt til dette show, mens du udforsker
Afspil