A State of the Art Technology in Large Scale Underwater Monitoring

Pavoni G., Corsini M., Cignoni P.

underwater monitoring  automatic recognition  human-in-the-loop  semantic segmentation  deep learning 

In recent decades, benthic populations have been subjected to recurrent episodes of mass mortality. These events have been blamed in part on declining water quality and elevated water temperatures (see Figure 1) correlated to global climate change. Ecosystems are enhanced by the presence of species with three-dimensional growth. The study of the growth, resilience, and recovery capability of those species provides valuable information on the conservation status of entire habitats. We discuss here a state-of-the art solution to speed up the monitoring of benthic population through the automatic or assisted analysis of underwater visual data.

Source: ERCIM news 2020 (2020): 17–18.

Publisher: ERCIM., Le Chesnay