FishSnap - Fishial Recognition 1.0

The mobile image recognition application utilizes a custom fish category dataset as a pre-trained model for Core ML, enabling users to effectively classify fish species from photographs.

This innovation provides smaller and underfunded fishers with an efficient tool to evaluate the nature and value of their catch, while also facilitating the tracking of fish locations through scanning. The data collected can significantly contribute to aquatic marine studies and enhance the machine learning capabilities of the image recognition system.

A notable achievement, this application was awarded the Fishackathon 2018 in New York City for its potential to reduce human error and diminish reliance on costly fish surveys, thereby offering smaller-scale fishers a more accurate means of assessing their catches.

There is optimism that this tool will be embraced by regulatory and research bodies, as well as the private sector, to support the identification of fish species from citizen-science data contributions.

The application's design allows for flexible implementation, paving the way for the integration of additional features in the near future.