TagLab

TagLab

Developer(s)| ISTI - CNR
Stable release|

2023.1.23 / January 23, 2023; 17 months ago (2023-01-23)[1]

Written in| python
Operating system| Cross-platform
Type| Graphics software
License| GPL
Website| taglab.isti.cnr.it

TagLab [2] is an interactive software system for facilitating the precise annotation of benthic species in orthophoto of the bottom of the sea. TagLab can automatically extract statistical informations about the evolution of monitored species and it offers many tools for segmenting large images using CNN-based algorithms.

Taglab is used in many marine research centers for the monitoring of coral reef like the MOTE Marine Laboratory[3], the Hawaiʻi Institute of Marine Biology[4], National Oceanic and Atmospheric Administration[5], and Scripps Institution of Oceanography[6].

TagLab has won the 2023 VRVis Visual Computing Award [7] for being "an open-source software solution that mitigates technological disparities between labs and promotes shared data standards and protocols".

## References

1. ↑ "TagLab 2023.1.23 release notes". Official GitHub repository. 2023-02-24. https://github.com/cnr-isti-vclab/TagLab/releases/tag/v2023.1.23.
2. ↑ Pavoni, Gaia; Corsini, Massimiliano; Ponchio, Federico; Muntoni, Alessandro; Edwards, Clinton; Pedersen, Nicole; Sandin, Stuart; Cignoni, Paolo (2022). "TagLab: AI-assisted annotation for the fast and accurate semantic segmentation of coral reef orthoimages". Journal of Field Robotics 39 (3): 246–262. doi:10.1002/rob.22049.
3. ↑ Combs, Ian. "MOTE - Coral Reef Ecosystems Program". https://mote.org/research/internships/college-internship-program-overview/coral-reef-ecosystems-program.
4. ↑ "Hybrid Reef Coastal Erosion Project". 31 October 2016. https://coralreefecologylab.com/research/.
5. ↑ Costa, Bryan; Sweeney, Edward; Mendez, Arnold (October 2022). "Leveraging Artificial Intelligence to Annotate Marine Benthic Species and Habitats". Noaa Technical Memorandum Nos Nccos 306. doi:10.25923/7kgv-ba52.
6. ↑ Riegl, Bernhard, ed (2020). Population Dynamics of the Reef Crisis. Elsevier Science. pp. 174–177. ISBN 9780128215302.
7. ↑ "Gaia Pavoni and Thomas Höllt win VRVis Visual Computing Award". https://www.vrvis.at/en/news-events/awards/gaia-pavoni-and-thomas-hoellt-win-vrvis-visual-computing-award.

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