The hydrographic community stands at a pivotal moment where machine learning/AI applications offer transformative potential. However, this potential can only be realized through coordinated, purposeful collaboration. We need your expertise and commitment to:
- Build confidence in machine learning/AI applications across the hydrographic community
- Establish standardized metrics and benchmark datasets that enable fair algorithm comparison
- Bridge the critical expertise gap between AI specialists and experts in hydrography
- Address applications across multiple data types (multibeam, SDB, lidar, ICESat-2, ASV imagery etc.)
To facilitate meaningful progress, I've established a GitHub repository where we can:
- Track issues to generate ideas for focused discussion
- Consolidate and organize proposals in one central location
- Identify concrete work items with actual consequences for our field
Repository link: CCOMJHC/MLHWG: Machine Learning in Hydrography Working Group
Please feel free to:
- Add issues for discussion topics you believe deserve our collective attention
- Recruit additional colleagues whose expertise could strengthen our initiative
This is volunteer work that requires commitment, but the potential impact on our field is substantial.