This EFMZV project VISIM aims to introduce Machine Vision in the Belgian beam trawl fishery, using self-sampling. The aim is more and better data collection on catches and discards in this particular fishery. The researchers are also counting on more data for the so-called data-limited fish species, such as turbot and brill, among others. The Machine Vision technology is expected to strengthen and facilitate the required collaborations between scientist and fishermen.
The researchers plan to work together with the crew of the Z483, a Belgian beam trawler. On this vessel we are testing the extent to which we can achieve accurate length measurement and species recognition of fish passing by on a conveyor belt using both classical image recognition methods and artificial intelligence (AI). We are investigating the accuracy of the system and the possibilities and problems of implementation.
Before this project began, only a small percentage of the catches of the Belgian fleet were documented by ILVO. A shortage of data on fish species such as turbot, brill and certain ray species makes it very difficult to estimate their distribution and densities in the fishing areas. The implementation of a more efficient, faster, automated system for data collection aboard fishing vessels can remedy this. Improved data sets are also important for the fisherman: over time, he will know better where the best fishing grounds are at any given time, based on length distributions per catch.
|Effective start/end date||1/07/19 → 31/12/20|