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MHKDR Data Management and Best Practices for Submitters and Curators

Resources for MHKDR data submitters and curators, including training videos, step-by-step guides on data submission, and detailed documentation of the MHKDR. The Data Management and Submission Best Practices document also contains API access and metadata schema information for dev...
Weers, J. et al National Renewable Energy Laboratory
Dec 15, 2021
3 Resources
0 Stars
Publicly accessible

Fish Detection AI, optic and sonar-trained object detection models

The Fish Detection AI project aims to improve the efficiency of fish monitoring around marine energy facilities to comply with regulatory requirements. Despite advancements in computer vision, there is limited focus on sonar images, identifying small fish with unlabeled data, and ...
Slater, K. et al Water Power Technology Office
Jun 25, 2014
12 Resources
0 Stars
In curation

TEAMER: Experimental Validation and Analysis of Deep Reinforcement Learning Control for Wave Energy Converters

Through this TEAMER project, Michigan Technological University (MTU) collaborated with Oregon State University (OSU) to test the performance of a Deep Reinforcement Learning (DRL) control in the wave tank. Unlike model-based controls, DRL control is model-free and can directly max...
Zou, S. et al Michigan Technological University
Feb 17, 2025
6 Resources
0 Stars
In progress
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  • The MHKDR is the submission point for all data collected from research funded by the U.S. Department of Energy's Marine and Hydrokinetic Power Program.
  • Content is available under Creative Commons Attribution 4.0 unless otherwise noted.

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